awesome-domain-adaptation

This repo is a collection of AWESOME things about domain adaptation, including papers, code, etc. Feel free to star and fork.

Contents

• awesome-domain-adaptation
• Contents
• Papers
  • Survey
  • Theory
  • Explainable
  • Unsupervised DA
    • Adversarial Methods
    • Distance-based Methods
    • Information-based Methods
    • Optimal Transport
    • Incremental Methods
    • Semi-Supervised-Learning-Based Methods
    • Self-training-Based Methods
    • Self-Supervised Methods
    • Transformer-based Methods
    • Other Methods
  • Semi-supervised DA
  • Weakly-Supervised DA
  • Zero-shot DA
  • One-shot DA
  • Few-shot UDA
  • Few-shot DA
  • Partial DA
  • Open Set DA
  • Universal DA
  • Open Compound DA
  • Multi Source DA
  • Multi Target DA
  • Incremental DA
  • Multi Step DA
  • Heterogeneous DA
  • Target-agnostic DA
  • Federated DA
  • Continuously Indexed DA
  • Source Free DA
  • Active DA
  • Generalized Domain Adaptation
  • Model Selection
  • Other Transfer Learning Paradigms
    • Domain Generalization
    • Domain Randomization
    • Transfer Metric Learning
    • Knowledge Transfer
    • Others
  • Applications
    • Object Detection
    • Semantic Segmentation
    • Person Re-identification
    • Sim-to-Real Transfer
    • Video Domain Adaptation
    • Medical Related
    • Monocular Depth Estimation
    • 3D
    • Fine-Grained Domain
    • LiDAR
    • Remote Sensing
    • Others
  • Benchmarks
• Library
• Lectures and Tutorials
• Other Resources

Papers

Survey

Arxiv

• Video Unsupervised Domain Adaptation with Deep Learning: A Comprehensive Survey [17 Nov 2022] [project]
• A Survey on Deep Domain Adaptation for LiDAR Perception [7 Jun 2021]
• A Comprehensive Survey on Transfer Learning [7 Nov 2019]
• Transfer Adaptation Learning: A Decade Survey [12 Mar 2019]
• A review of single-source unsupervised domain adaptation [16 Jan 2019]
• An introduction to domain adaptation and transfer learning [31 Dec 2018]
• A Survey of Unsupervised Deep Domain Adaptation [6 Dec 2018]
• Transfer Learning for Cross-Dataset Recognition: A Survey [2017]
• Domain Adaptation for Visual Applications: A Comprehensive Survey [2017]

Journal

• Survey on Unsupervised Domain Adaptation for Semantic Segmentation for Visual Perception in Automated Driving [IEEE Access 2023]
• A Review of Single-Source Deep Unsupervised Visual Domain Adaptation [TNNLS 2020]
• Deep Visual Domain Adaptation: A Survey [Neurocomputing 2018]
• A Survey on Deep Transfer Learning [ICANN2018]
• Visual domain adaptation: A survey of recent advances [2015]

Theory

Arxiv

• A Theory of Label Propagation for Subpopulation Shift [22 Feb 2021]
• A General Upper Bound for Unsupervised Domain Adaptation [3 Oct 2019]
• On Deep Domain Adaptation: Some Theoretical Understandings [arXiv 15 Nov 2018]

Conference

• Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift [NeurIPS 2020]
• Bridging Theory and Algorithm for Domain Adaptation [ICML2019] [Pytorch]
• On Learning Invariant Representation for Domain Adaptation [ICML2019] [code]
• Unsupervised Domain Adaptation Based on Source-guided Discrepancy [AAAI2019]
• Learning Bounds for Domain Adaptation [NIPS2007]
• Analysis of Representations for Domain Adaptation [NIPS2006]

Journal

• On a Regularization of Unsupervised Domain Adaptation in RKHS [ACHA2021]
• Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice [TPAMI2020] [PyTroch]
• On generalization in moment-based domain adaptation [AMAI2020]
• A theory of learning from different domains [ML2010]

Explainable

Conference

• Visualizing Adapted Knowledge in Domain Transfer [CVPR2021] [Pytorch]

Unsupervised DA

Adversarial Methods

Conference

• SPA: A Graph Spectral Alignment Perspective for Domain Adaptation [NeurIPS 2023] [Pytorch]
• Reusing the Task-specific Classifier as a Discriminator: Discriminator-free Adversarial Domain Adaptation [CVPR2022] [Pytorch]
• A Closer Look at Smoothness in Domain Adversarial Training [ICML2022] [Pytorch]
• ToAlign: Task-oriented Alignment for Unsupervised Domain Adaptation [NeurIPS2021] [Pytorch]
• Adversarial Unsupervised Domain Adaptation With Conditional and Label Shift: Infer, Align and Iterate [ICCV2021]
• Gradient Distribution Alignment Certificates Better Adversarial Domain Adaptation [ICCV2021]
• Re-energizing Domain Discriminator with Sample Relabeling for Adversarial Domain Adaptation [ICCV2021]
• Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation [CVPR2021] [Pytorch]
• MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptation [CVPR2021] [Pytorch]
• Self-adaptive Re-weighted Adversarial Domain Adaptation [IJCAI2020]
• DIRL: Domain-Invariant Reperesentation Learning Approach for Sim-to-Real Transfer [CoRL2020] [Project]
• SSA-DA: Bi-dimensional feature alignment for cross-domain object detection [ECCV Workshop 2020]
• Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation [ECCV2020] [PyTorch]
• MCAR: Adaptive object detection with dual multi-label prediction [ECCV2020]
• Gradually Vanishing Bridge for Adversarial Domain Adaptation [CVPR2020] [Pytorch]
• Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation [ICML2020] [Pytorch]
• Adversarial-Learned Loss for Domain Adaptation [AAAI2020]
• Structure-Aware Feature Fusion for Unsupervised Domain Adaptation [AAAI2020]
• Adversarial Domain Adaptation with Domain Mixup [AAAI2020] [Pytorch]
• Discriminative Adversarial Domain Adaptation [AAAI2020] [Pytorch]
• Bi-Directional Generation for Unsupervised Domain Adaptation [AAAI2020]
• Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning [ICASSP 2020]
• Curriculum based Dropout Discriminator for Domain Adaptation [BMVC2019] [Project]
• Unifying Unsupervised Domain Adaptation and Zero-Shot Visual Recognition [IJCNN2019] [Matlab]
• Transfer Learning with Dynamic Adversarial Adaptation Network [ICDM2019]
• Joint Adversarial Domain Adaptation [ACM MM2019]
• Cycle-consistent Conditional Adversarial Transfer Networks [ACM MM2019] [Pytorch]
• Learning Disentangled Semantic Representation for Domain Adaptation [IJCAI2019] [Tensorflow]
• Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation [ICML2019] [Pytorch]
• Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers [ICML2019] [Pytorch]
• Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation [ICCV2019] [PyTorch]
• Cluster Alignment with a Teacher for Unsupervised Domain Adaptation [ICCV2019] [Tensorflow]
• Unsupervised Domain Adaptation via Regularized Conditional Alignment [ICCV2019]
• Attending to Discriminative Certainty for Domain Adaptation [CVPR2019] [Project]
• GCAN: Graph Convolutional Adversarial Network for Unsupervised Domain Adaptation [CVPR2019]
• Domain-Symmetric Networks for Adversarial Domain Adaptation [CVPR2019] [Pytorch]
• DLOW: Domain Flow for Adaptation and Generalization [CVPR2019 Oral]
• Progressive Feature Alignment for Unsupervised Domain Adaptation [CVPR2019] [Tensorflow]
• Gotta Adapt ’Em All: Joint Pixel and Feature-Level Domain Adaptation for Recognition in the Wild [CVPR2019]
• Looking back at Labels: A Class based Domain Adaptation Technique [IJCNN2019] [Project]
• Consensus Adversarial Domain Adaptation [AAAI2019]
• Transferable Attention for Domain Adaptation [AAAI2019]
• Exploiting Local Feature Patterns for Unsupervised Domain Adaptation [AAAI2019]
• Augmented Cyclic Adversarial Learning for Low Resource Domain Adaptation [ICLR2019]
• Conditional Adversarial Domain Adaptation [NIPS2018] [Pytorch(official)] [Pytorch(third party)]
• Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model [ECCV2018]
• Deep Adversarial Attention Alignment for Unsupervised Domain Adaptation: the Benefit of Target Expectation Maximization [ECCV2018]
• Learning Semantic Representations for Unsupervised Domain Adaptation [ICML2018] [TensorFlow(Official)]
• CyCADA: Cycle-Consistent Adversarial Domain Adaptation [ICML2018] [Pytorch(official)]
• From source to target and back: Symmetric Bi-Directional Adaptive GAN [CVPR2018] [Keras(Official)] [Pytorch]
• Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation [CVPR2018] [Tensorflow]
• Maximum Classifier Discrepancy for Unsupervised Domain Adaptation [CVPR2018] [Pytorch(Official)]
• Adversarial Feature Augmentation for Unsupervised Domain Adaptation [CVPR2018] [TensorFlow(Official)]
• Duplex Generative Adversarial Network for Unsupervised Domain Adaptation [CVPR2018] [Pytorch(Official)]
• Generate To Adapt: Aligning Domains using Generative Adversarial Networks [CVPR2018] [Pytorch(Official)]
• Image to Image Translation for Domain Adaptation [CVPR2018]
• Unsupervised Domain Adaptation with Similarity Learning [CVPR2018]
• Conditional Generative Adversarial Network for Structured Domain Adaptation [CVPR2018]
• Collaborative and Adversarial Network for Unsupervised Domain Adaptation [CVPR2018] [Pytorch]
• Re-Weighted Adversarial Adaptation Network for Unsupervised Domain Adaptation [CVPR2018]
• Multi-Adversarial Domain Adaptation [AAAI2018] [Caffe(Official)]
• Wasserstein Distance Guided Representation Learning for Domain Adaptation [AAAI2018] [TensorFlow(official)] [Pytorch]
• Incremental Adversarial Domain Adaptation for Continually Changing Environments [ICRA2018]
• Adversarial Dropout Regularization [ICLR2018]
• A DIRT-T Approach to Unsupervised Domain Adaptation [ICLR2018 Poster] [Tensorflow(Official)]
• Label Efficient Learning of Transferable Representations acrosss Domains and Tasks [NIPS2017] [Project]
• Adversarial Discriminative Domain Adaptation [CVPR2017] [Tensorflow(Official)] [Pytorch]
• Unsupervised Pixel–Level Domain Adaptation with Generative Adversarial Networks [CVPR2017] [Tensorflow(Official)] [Pytorch]
• Domain Separation Networks [NIPS2016]
• Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation [ECCV2016]
• Domain-Adversarial Training of Neural Networks [JMLR2016]
• Unsupervised Domain Adaptation by Backpropagation [ICML2015] [Caffe(Official)] [Tensorflow] [Pytorch]

Journal

• Incremental Unsupervised Domain-Adversarial Training of Neural Networks [TNNLS 2020]
• Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice [TPAMI2020] [PyTroch]
• Adversarial Learning and Interpolation Consistency for Unsupervised Domain Adaptation [IEEE ACCESS]
• TarGAN: Generating target data with class labels for unsupervised domain adaptation [Knowledge-Based Systems]

Arxiv

• Bi-Directional Generation for Unsupervised Domain Adaptation [12 Feb 2020]
• Enlarging Discriminative Power by Adding an Extra Class in Unsupervised Domain Adaptation [19 Feb 2020] [Tensorflow]
• Learning Domain Adaptive Features with Unlabeled Domain Bridges [10 Dec 2019]
• Reducing Domain Gap via Style-Agnostic Networks [25 Oct 2019]
• Generalized Domain Adaptation with Covariate and Label Shift CO-ALignment [23 Oct 2019]
• Adversarial Variational Domain Adaptation [25 Sep 2019]
• Contrastively Smoothed Class Alignment for Unsupervised Domain Adaptation [arXiv 13 Sep 2019]
• SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation [arXiv 11 Jun 2019]
• Joint Semantic Domain Alignment and Target Classifier Learning for Unsupervised Domain Adaptation [arXiv 10 Jun 2019]
• Adversarial Domain Adaptation Being Aware of Class Relationships [arXiv 28 May 2019]
• Domain-Invariant Adversarial Learning for Unsupervised Domain Adaption [arXiv 30 Nov 2018]
• Unsupervised Domain Adaptation using Deep Networks with Cross-Grafted Stacks [arXiv 17 Feb 2019]
• DART: Domain-Adversarial Residual-Transfer Networks for Unsupervised Cross-Domain Image Classification [arXiv 30 Dec 2018]
• Unsupervised Domain Adaptation using Generative Models and Self-ensembling [arXiv 2 Dec 2018]
• Domain Confusion with Self Ensembling for Unsupervised Adaptation [arXiv 10 Oct 2018]
• Improving Adversarial Discriminative Domain Adaptation [arXiv 10 Sep 2018]
• M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning [arXiv 6 Jul 2018] [Pytorch(official)]
• Factorized Adversarial Networks for Unsupervised Domain Adaptation [arXiv 4 Jun 2018]
• DiDA: Disentangled Synthesis for Domain Adaptation [arXiv 21 May 2018]
• Unsupervised Domain Adaptation with Adversarial Residual Transform Networks [arXiv 25 Apr 2018]
• Causal Generative Domain Adaptation Networks [arXiv 28 Jun 2018]

Distance-based Methods

Journal

• Transferable Representation Learning with Deep Adaptation Networks [TPAMI]
• Robust unsupervised domain adaptation for neural networks via moment alignment [InfSc2019]

Conference

• Domain Conditioned Adaptation Network [AAAI2020] [Pytorch]
• HoMM: Higher-order Moment Matching for Unsupervised Domain Adaptation [AAAI2020] [Tensorflow]
• Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation [ICCV2019]
• Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation [AAAI2019]
• Residual Parameter Transfer for Deep Domain Adaptation [CVPR2018]
• Deep Asymmetric Transfer Network for Unbalanced Domain Adaptation [AAAI2018]
• Central Moment Discrepancy for Unsupervised Domain Adaptation [ICLR2017], [InfSc2019], [code]
• Deep CORAL: Correlation Alignment for Deep Domain Adaptation [ECCV2016]
• Learning Transferable Features with Deep Adaptation Networks [ICML2015][code]
• Unsupervised Domain Adaptation with Residual Transfer Networks [NIPS2016] [code]
• Deep Transfer Learning with Joint Adaptation Networks [ICML2017] [code]

Arxiv

• Deep Domain Confusion: Maximizing for Domain Invariance [Arxiv 2014]

Information-based Methods

• Hypothesis Disparity Regularized Mutual Information Maximization [AAAI2021]

Optimal Transport

Conference

• Global-Local Regularization Via Distributional Robustness [AISTATS2023] [Pytorch]
• MOST: Multi-Source Domain Adaptation via Optimal Transport for Student-Teacher Learning [UAI2021]
• LAMDA: Label Matching Deep Domain Adaptation [ICML2021]
• TIDOT: A Teacher Imitation Learning Approach for Domain Adaptation with Optimal Transport [IJCAI2021]
• Unbalanced minibatch Optimal Transport; applications to Domain Adaptation [ICML2021] [Pytorch]
• Graph Optimal Transport for Cross-Domain Alignment [ICML2020]
• Margin-aware Adversarial Domain Adaptation with Optimal Transport [ICML2020] [code]
• Metric Learning in Optimal Transport for Domain Adaptation [IJCAI2020]
• Reliable Weighted Optimal Transport for Unsupervised Domain Adaptation [CVPR2020]
• Enhanced Transport Distance for Unsupervised Domain Adaptation [CVPR2020] [Pytorch]
• Differentially Private Optimal Transport: Application to Domain Adaptation [IJCAI2019]
• DeepJDOT: Deep Joint distribution optimal transport for unsupervised domain adaptation [ECCV2018] [Keras]
• Joint Distribution Optimal Transportation for Domain Adaptation [NIPS2017] [python] [Python Optimal Transport Library]

Arxiv

• CDOT: Continuous Domain Adaptation using Optimal Transport [20 Sep 2019]

Incremental Methods

• Incremental Unsupervised Domain-Adversarial Training of Neural Networks [TNNLS 2020]

Semi-Supervised-Learning-Based Methods

• Label Propagation with Augmented Anchors: A Simple Semi-Supervised Learning baseline for Unsupervised Domain Adaptation [ECCV2020]
• Semi-supervised Models are Strong Unsupervised Domain Adaptation Learners [arXiv 2021][Pytorch]

Self-training-Based Methods

• Cycle Self-Training for Domain Adaptation [NeurIPS2021]
• Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark [ICCV Workshop 2021] [Pytorch]
• Instance Adaptive Self-Training for Unsupervised Domain Adaptation [ECCV 2020] [Pytorch]
• Self-training Avoids Using Spurious Features Under Domain Shift [NeurIPS 2020]
• Two-phase Pseudo Label Densification for Self-training based Domain Adaptation [ECCV2020]

Arxiv

• Probabilistic Contrastive Learning for Domain Adaptation [arXiv 20211] [Pytorch]
• Gradual Domain Adaptation via Self-Training of Auxiliary Models[arXiv 2021][Pytorch]

Self-Supervised Methods

Conference

• Self-Supervised CycleGAN for Object-Preserving Image-to-Image Domain Adaptation [ECCV2020]

Arxiv

• Unsupervised Domain Adaptation through Self-Supervision [arXiv 26 Sep 2019]

Transformer-based Methods

Conference

• Safe Self-Refinement for Transformer-Based Domain Adaptation [CVPR2022] [Pytorch

Other Methods

Conference

• Prior Knowledge Guided Unsupervised Domain Adaptation [ECCV2022] [Pytorch]
• Revisiting Unsupervised Domain Adaptation Models: a Smoothness Perspective [ACCV2022] [Pytorch]
• Reducing the Covariate Shift by Mirror Samples in Cross Domain Alignment [NeurIPS2021]
• Pareto Domain Adaptation [NeurIPS2021]
• ToAlign: Task-Oriented Alignment for Unsupervised Domain Adaptation [NeurIPS2021]
• A Prototype-Oriented Framework for Unsupervised Domain Adaptation [NeurIPS2021]
• Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning [NeurIPS2021]
• SENTRY: Selective Entropy Optimization via Committee Consistency for Unsupervised Domain Adaptation [ICCV2021]
• Transporting Causal Mechanisms for Unsupervised Domain Adaptation [ICCV2021]
• Semantic Concentration for Domain Adaptation [ICCV2021]
• FixBi: Bridging Domain Spaces for Unsupervised Domain Adaptation [CVPR2021]
• Domain Adaptation With Auxiliary Target Domain-Oriented Classifier [CVPR2021]
• Conditional Bures Metric for Domain Adaptation [CVPR2021]
• DRANet: Disentangling Representation and Adaptation Networks for Unsupervised Cross-Domain Adaptation [CVPR2021]
• Visualizing Adapted Knowledge in Domain Transfer [CVPR2021] [Pytorch]
• Instance Level Affinity-Based Transfer for Unsupervised Domain Adaptation [CVPR2021] [code coming soon]
• Dynamic Domain Adaptation for Efficient Inference [CVPR2021] [Pytorch]
• Transferable Semantic Augmentation for Domain Adaptation [CVPR2021] [Pytorch]
• MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptation [CVPR2021]
• DRANet: Disentangling Representation and Adaptation Networks for Unsupervised Cross-Domain Adaptation [CVPR2021]
• Dynamic Weighted Learning for Unsupervised Domain Adaptation [CVPR2021]
• Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift [NeurIPS 2020]
• Transferable Calibration with Lower Bias and Variance in Domain Adaptation [NeurIPS 2020]
• A Dictionary Approach to Domain-Invariant Learning in Deep Networks [NeurIPS 2020]
• Heuristic Domain Adaptation [NeurIPS2020] [Pytorch]
• Unsupervised Domain Adaptation for Semantic Segmentation of NIR Images through Generative Latent Search [ECCV2020][code]
• Mind the Discriminability: Asymmetric Adversarial Domain Adaptation [ECCV2020]
• Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation [ECCV2020]
• CSCL: Critical Semantic-Consistent Learning for Unsupervised Domain Adaptation [ECCV2020]
• Minimum Class Confusion for Versatile Domain Adaptation [ECCV2020]
• Partially-Shared Variational Auto-encoders for Unsupervised Domain Adaptation with Target Shift [ECCV2020] [Pytorch]
• Label Propagation with Augmented Anchors: A Simple Semi-Supervised Learning baseline for Unsupervised Domain Adaptation [ECCV2020] [PyTorch]
• Unsupervised Domain Adaptation via Structurally Regularized Deep Clustering [CVPR2020 Oral] [Pytorch]
• Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations [CVPR2020 Oral] [Pytorch]
• Unsupervised Domain Adaptation With Hierarchical Gradient Synchronization [CVPR2020]
• Spherical Space Domain Adaptation With Robust Pseudo-Label Loss [CVPR2020] [Pytorch]
• Stochastic Classifiers for Unsupervised Domain Adaptation [CVPR2020]
• Structure Preserving Generative Cross-Domain Learning [CVPR2020]
• Light-weight Calibrator: A Separable Component for Unsupervised Domain Adaptation [CVPR2020] [code]
• Domain Adaptive Multiflow Networks [ICLR2020]
• Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment [AAAI2020]
• Visual Domain Adaptation by Consensus-based Transfer to Intermediate Domain [Paper]
• Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling [AAAI2020] [Matlab]
• CUDA: Contradistinguisher for Unsupervised Domain Adaptation [ICDM2019]
• Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment [ICML2019]
• Batch Weight for Domain Adaptation With Mass Shift [ICCV2019]
• Switchable Whitening for Deep Representation Learning [ICCV2019] [pytorch]
• Confidence Regularized Self-Training [ICCV2019 Oral] [Pytorch]
• Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation [ICCV2019] [Pytorch(official)]
• Transferrable Prototypical Networks for Unsupervised Domain Adaptation [CVPR2019(Oral)]
• Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation [CVPR2019]
• Unsupervised Domain Adaptation using Feature-Whitening and Consensus Loss [CVPR 2019] [Pytorch]
• Domain Specific Batch Normalization for Unsupervised Domain Adaptation [CVPR2019] [Pytorch]
• AdaGraph: Unifying Predictive and Continuous Domain Adaptation through Graphs [CVPR2019] [Pytorch]
• Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach [CVPR2019] [Project]
• Contrastive Adaptation Network for Unsupervised Domain Adaptation [CVPR2019] [Pytorch]
• Distant Supervised Centroid Shift: A Simple and Efficient Approach to Visual Domain Adaptation [CVPR2019]
• Unsupervised Domain Adaptation via Calibrating Uncertainties [CVPRW2019]
• Bayesian Uncertainty Matching for Unsupervised Domain Adaptation [IJCAI2019]
• Unsupervised Domain Adaptation for Distance Metric Learning [ICLR2019]
• Co-regularized Alignment for Unsupervised Domain Adaptation [NIPS2018]
• Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation [TIP 2018]
• Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation [ECCV2018]
• Aligning Infinite-Dimensional Covariance Matrices in Reproducing Kernel Hilbert Spaces for Domain Adaptation [CVPR2018]
• Unsupervised Domain Adaptation with Distribution Matching Machines [AAAI2018]
• Learning to cluster in order to transfer across domains and tasks [ICLR2018] [Bolg] [Pytorch]
• Self-Ensembling for Visual Domain Adaptation [ICLR2018]
• Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation [ICLR2018] [TensorFlow]
• Associative Domain Adaptation [ICCV2017] [TensorFlow] [Pytorch]
• AutoDIAL: Automatic DomaIn Alignment Layers [ICCV2017]
• Asymmetric Tri-training for Unsupervised Domain Adaptation [ICML2017] [TensorFlow]
• Learning Transferrable Representations for Unsupervised Domain Adaptation [NIPS2016]

Journal

• Target-Independent Domain Adaptation for WBC Classification using Generative Latent Search [IEEE TMI 2020][code]
• Adaptive Batch Normalization for practical domain adaptation [Pattern Recognition(2018)]
• Unsupervised Domain Adaptation by Mapped Correlation Alignment [IEEE ACCESS]

Arxiv

• Low-confidence Samples Matter for Domain Adaptation [6 Feb 2022] [Pytorch]
• Improving Unsupervised Domain Adaptation with Variational Information Bottleneck [21 Nov 2019]
• Deep causal representation learning for unsupervised domain adaptation [28 Oct 2019]
• Domain-invariant Learning using Adaptive Filter Decomposition [25 Sep 2019]
• Discriminative Clustering for Robust Unsupervised Domain Adaptation [arXiv 30 May 2019]
• Virtual Mixup Training for Unsupervised Domain Adaptation [arXiv on 24 May 2019] [Tensorflow]
• Learning Smooth Representation for Unsupervised Domain Adaptation [arXiv 26 May 2019]
• Towards Self-similarity Consistency and Feature Discrimination for Unsupervised Domain Adaptation [arXiv 13 Apr 2019]
• Easy Transfer Learning By Exploiting Intra-domain Structures [arXiv 2 Apr 2019]
• Domain Discrepancy Measure Using Complex Models in Unsupervised Domain Adaptation [arXiv 30 Jan 2019]
• Domain Alignment with Triplets [arXiv 22 Jan 2019]
• Deep Discriminative Learning for Unsupervised Domain Adaptation [arXiv 17 Nov 2018]

Foundation-Models based DA

Conference

• POUF: Prompt-oriented unsupervised fine-tuning for large pre-trained models [ICML2023] [Pytorch]

Semi-supervised DA

Conference

• Semi-Supervised Domain Adaptation With Source Label Adaptation [CVPR 2023]
• Multi-level Consistency Learning for Semi-supervised Domain Adaptation [IJCAI 2022]
• AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation [ICLR 2022]
• CLDA: Contrastive Learning for Semi-Supervised Domain Adaptation [NeurIPS]
• Deep Co-Training With Task Decomposition for Semi-Supervised Domain Adaptation [ICCV2021]
• ECACL: A Holistic Framework for Semi-Supervised Domain Adaptation [ICCV2021]
• Cross-Domain Adaptive Clustering for Semi-Supervised Domain Adaptation [CVPR2021]
• Semi-supervised Domain Adaptation based on Dual-level Domain Mixing for Semantic Segmentation [CVPR2021]
• Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation [CVPR2021]
• Improving Semi-Supervised Domain Adaptation Using Effective Target Selection and Semantics [CVPRW2021] [Code]
• Attract, Perturb, and Explore: Learning a Feature Alignment Network for Semi-supervised Domain Adaptation [ECCV2020]
• Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation [ECCV2020]
• Bidirectional Adversarial Training for Semi-Supervised Domain Adaptation [IJCAI2020]
• Semi-supervised Domain Adaptation via Minimax Entropy [ICCV2019] [Pytorch]

Journal

• Context-guided entropy minimization for semi-supervised domain adaptation [Neural Networks] [pytorch]

Arxiv

• Pred&Guide: Labeled Target Class Prediction for Guiding Semi-Supervised Domain Adaptation [22 Nov 2022]
• MiCo: Mixup Co-Training for Semi-Supervised Domain Adaptation [ 24 Jul 2020]
• Opposite Structure Learning for Semi-supervised Domain Adaptation [6 Feb 2020]
• Reducing Domain Gap via Style-Agnostic Networks [25 Oct 2019]

Weakly-Supervised DA

Conference

• Towards Accurate and Robust Domain Adaptation under Noisy Environments [IJCAI2020]
• Weakly Supervised Open-set Domain Adaptation by Dual-domain Collaboration [CVPR2019]
• Transferable Curriculum for Weakly-Supervised Domain Adaptation [AAAI2019]

Arxiv

• Butterfly: Robust One-step Approach towards Wildly-unsupervised Domain Adaptation [arXiv on 19 May 2019]

Zero-shot DA

Conference

• Collaborative Learning With Disentangled Features for Zero-Shot Domain Adaptation [ICCV2021]
• Zero-Shot Day-Night Domain Adaptation with a Physics Prior [ICCV2021]
• High Resolution Zero-Shot Domain Adaptation of Synthetically Rendered Face Images [ECCV2020]
• Adversarial Learning for Zero-shot Domain Adaptation [ECCV2020]
• HGNet: Hybrid Generative Network for Zero-shot Domain Adaptation [ECCV2020]
• Zero-shot Domain Adaptation Based on Attribute Information [ACML2019]
• Conditional Coupled Generative Adversarial Networks for Zero-Shot Domain Adaptation [ICCV2019]
• Generalized Zero-Shot Learning with Deep Calibration Network [NIPS2018]
• Zero-Shot Deep Domain Adaptation [ECCV2018]

One-shot DA

Conference

• Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation [NeurIPS2020] [Pytorch]
• One-Shot Adaptation of Supervised Deep Convolutional Models [ICLR Workshop 2014]

Arxiv

• One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning [arxiv]

Few-shot UDA

Conference

• Prototypical Cross-domain Self-supervised Learning for Few-shot Unsupervised Domain Adaptation [CVPR2021] [Pytorch] [Project]

Arxiv

• Cross-domain Self-supervised Learning for Domain Adaptation with Few Source Labels [arXiv 18 Mar 2020]

Few-shot DA

Conference

• Domain-Adaptive Few-Shot Learning[WACV2021] [Pytorch]
• Few-shot Domain Adaptation by Causal Mechanism Transfer [ICML2020] [Pytorch]
• Few-Shot Adaptive Faster R-CNN [CVPR2019]
• d-SNE: Domain Adaptation using Stochastic Neighborhood Embedding [CVPR2019 Oral]
• Few-Shot Adversarial Domain Adaptation [NIPS2017]

Arxiv

• Feature transformation ensemble model with batch spectral regularization for cross-domain few-shot classification [arXiv 18 May 2020] [Pytorch]
• Ensemble model with batch spectral regularization and data blending for cross-domain few-shot learning with unlabeled data [arXiv 8 June 2020] [Pytorch]

Partial DA

Conference

• Implicit Semantic Response Alignment for Partial Domain Adaptation [NeurIPS2021] [Pytorch]
• Adversarial Reweighting for Partial Domain Adaptation [NeurIPS2021]
• A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation [ECCV2020] [Pytorch]
• Discriminative Partial Domain Adversarial Network [ECCV2020]
• Selective Transfer With Reinforced Transfer Network for Partial Domain Adaptation [CVPR2020]
• Adaptively-Accumulated Knowledge Transfer for Partial Domain Adaptation [ACM MM2020]
• Multi-Weight Partial Domain Adaptation [BMVC2019]
• Learning to Transfer Examples for Partial Domain Adaptation [CVPR2019] [Pytorch]
• Partial Adversarial Domain Adaptation [ECCV2018] [Pytorch(Official)]
• Importance Weighted Adversarial Nets for Partial Domain Adaptation [CVPR2018] [Caffe]
• Partial Transfer Learning with Selective Adversarial Networks [CVPR2018][paper weekly] [Pytorch(Official) & Caffe(official)]

Journal

• Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice [TPAMI2020] [PyTroch]

Arxiv

• Select, Label, and Mix: Learning Discriminative Invariant Feature Representations for Partial Domain Adaptation [arXiv 06 Dec 2020]
• Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice [20 Feb 2020] [PyTroch]
• Tackling Partial Domain Adaptation with Self-Supervision [arXiv 12 Jun 2019]
• Domain Adversarial Reinforcement Learning for Partial Domain Adaptation [arXiv 10 May 2019]

Open Set DA

Conference

• Towards Novel Target Discovery Through Open-Set Domain Adaptation [ICCV2021]
• On the Effectiveness of Image Rotation for Open Set Domain Adaptation [ECCV2020] [Pytorch]
• Multi-Source Open-Set Deep Adversarial Domain Adaptation [ECCV2020]
• Progressive Graph Learning for Open-Set Domain Adaptation [ICML2020] [Pytorch]
• Joint Partial Optimal Transport for Open Set Domain Adaptation [IJCAI2020]
• Exploring Category-Agnostic Clusters for Open-Set Domain Adaptation [CVPR2020]
• Towards Inheritable Models for Open-Set Domain Adaptation [CVPR 2020] [Project]
• Attract or Distract: Exploit the Margin of Open Set [ICCV2019] [code]
• Separate to Adapt: Open Set Domain Adaptation via Progressive Separation [CVPR2019] [Pytorch]
• Weakly Supervised Open-set Domain Adaptation by Dual-domain Collaboration [CVPR2019]
• Learning Factorized Representations for Open-set Domain Adaptation [ICLR2019]
• Open Set Domain Adaptation by Backpropagation [ECCV2018] [Pytorch(Official)] [Tensorflow] [Pytorch]
• Open Set Domain Adaptation [ICCV2017]

Journal

• Open-set domain adaptation by deconfounding domain gaps [Applied Intelligence 2022]
• Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice [TPAMI2020] [PyTroch]
• Adversarial Network with Multiple Classifiers for Open Set Domain Adaptation [IEEE TMM] [Pytorch]

Arxiv

• Collaborative Training of Balanced Random Forests for Open Set Domain Adaptation [10 Feb 2020]
• Known-class Aware Self-ensemble for Open Set Domain Adaptation [3 May 2019]

Universal DA

Conference

• Universal Domain Adaptation for Robust Handling of Distributional Shifts in NLP [EMNLP 2023 Findings]
• Subsidiary Prototype Alignment for Universal Domain Adaptation [NeurIPS2022] [Project Page]
• OVANet: One-vs-All Network for Universal Domain Adaptation [ICCV2021]
• Active Universal Domain Adaptation [ICCV 2021]
• Domain Consensus Clustering for Universal Domain Adaptation [CVPR 2021] [Pytorch]
• Divergence Optimization for Noisy Universal Domain Adaptation [CVPR2021]
• Universal Domain Adaptation through Self Supervision [NeurIPS 2020] [Pytorch]
• Learning to Detect Open Classes for Universal Domain Adaptation [ECCV2020] [code]
• Universal Source-Free Domain Adaptation [CVPR2020] [Project]
• Universal Domain Adaptation [CVPR2019] [Pytorch]

Journal

• Universal Model Adaptation by Style Augmented Open-set Consistency [Applied Intelligence 2023]

Arxiv

• Universal Multi-Source Domain Adaptation [5 Nov 2020]
• A Sample Selection Approach for Universal Domain Adaptation [14 Jan 2020]

Open Compound DA

Conference

• Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation [NeurIPS2020]
• Open Compound Domain Adaptation [CVRP2020 Oral] [Pytorch]

Journal

• Source-Free Open Compound Domain Adaptation in Semantic Segmentation [TCSVT 2022]

Multi Source DA

Conference

• Confident Anchor-Induced Multi-Source Free Domain Adaptation [NeurIPS2021] [code is coming soon]
• mDALU: Multi-Source Domain Adaptation and Label Unification With Partial Datasets [ICCV2021]
• STEM: An Approach to Multi-Source Domain Adaptation With Guarantees [ICCV2021]
• T-SVDNet: Exploring High-Order Prototypical Correlations for Multi-Source Domain Adaptation [ICCV2021]
• Multi-Source Domain Adaptation for Object Detection [ICCV2021]
• Information-Theoretic Regularization for Multi-Source Domain Adaptation [ICCV2021]
• Partial Feature Selection and Alignment for Multi-Source Domain Adaptation [CVPR2021]
• Wasserstein Barycenter for Multi-Source Domain Adaptation [CVPR2021] [Code]
• Unsupervised Multi-source Domain Adaptation Without Access to Source Data [CVPR2021]
• Dynamic Transfer for Multi-Source Domain Adaptation [CVPR2021] [Pytorch]
• Multi-Source Domain Adaptation with Collaborative Learning for Semantic Segmentation [CVPR2021]
• MOST: Multi-Source Domain Adaptation via Optimal Transport for Student-Teacher Learning [UAI2021]
• Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark [ICCV Workshop 2021] [Pytorch]
• Your Classifier can Secretly Suffice Multi-Source Domain Adaptation [NeurIPS 2020] [Project]
• Multi-Source Open-Set Deep Adversarial Domain Adaptation [ECCV2020]
• Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation [ECCV2020]
• Multi-Source Open-Set Deep Adversarial Domain Adaptation [ECCV2020]
• Curriculum Manager for Source Selection in Multi-Source Domain Adaptation [ECCV2020]
• Domain Aggregation Networks for Multi-Source Domain Adaptation [ICML2020]
• Learning to Combine: Knowledge Aggregation for Multi-Source Domain Adaptation [ECCV2020] [Pytorch]
• Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits [AAAI2020]
• Adversarial Training Based Multi-Source Unsupervised Domain Adaptation for Sentiment Analysis [AAAI2020]
• Multi-source Domain Adaptation for Visual Sentiment Classification [AAAI2020]
• Multi-source Distilling Domain Adaptation [AAAI2020] [code]
• Multi-source Domain Adaptation for Semantic Segmentation [NeurlPS2019] [Pytorch]
• Moment Matching for Multi-Source Domain Adaptation [ICCV2019] [Pytorch]
• Multi-Domain Adversarial Learning [ICLR2019] [Torch]
• Algorithms and Theory for Multiple-Source Adaptation [NIPS2018]
• Adversarial Multiple Source Domain Adaptation [NIPS2018] [Pytorch]
• Boosting Domain Adaptation by Discovering Latent Domains [CVPR2018] [Caffe] [Pytorch]
• Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift [CVPR2018] [Pytorch]

Journal

• Graphical Modeling for Multi-Source Domain Adaptation [TPAMI 2022] [Pytorch]
• Unsupervised sentiment analysis by transferring multi-source knowledge[Cognitive Computation]
• A survey of multi-source domain adaptation [Information Fusion]

Arxiv

• Mutual learning network for multi-source domain adaptation [arXiv]
• Domain Adaptive Ensemble Learning [arXiv]
• Multi-Source Domain Adaptation and Semi-Supervised Domain Adaptation with Focus on Visual Domain Adaptation Challenge 2019 [14 Oct 2019]

Multi Target DA

Conference

• CoNMix for Source-free Single and Multi-target Domain Adaptation [WACV2022] [Pytorch]
• Curriculum Graph Co-Teaching for Multi-Target Domain Adaptation [CVPR2021] [Pytorch]
• Multi-Target Domain Adaptation with Collaborative Consistency Learning [CVPR2021]

Arxiv

• Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach [arXiv]

Incremental DA

Conference

• Lifelong Domain Adaptation via Consolidated Internal Distribution [NeurIPS2021]
• Continual Adaptation of Visual Representations via Domain Randomization and Meta-learning [CVPR2021]
• ConDA: Continual Unsupervised Domain Adaptation [CVPR2021]
• Gradient Regularized Contrastive Learning for Continual Domain Adaptation [AAAI2021]
• Gradual Domain Adaptation without Indexed Intermediate Domains [NeurIPS2021]
• Learning to Adapt to Evolving Domains [NeurIPS 2020] [Pytorch]
• Class-Incremental Domain Adaptation [ECCV2020]
• Incremental Adversarial Domain Adaptation for Continually Changing Environments [ICRA2018]
• Continuous Manifold based Adaptation for Evolving Visual Domains [CVPR2014]

Multi Step DA

Arxiv

• Adversarial Domain Adaptation for Stance Detection [arXiv]
• Ensemble Adversarial Training: Attacks and Defenses [arXiv]

Conference

• Distant domain transfer learning [AAAI2017]

Heterogeneous DA

Conference

• Domain Adaptive Classification on Heterogeneous Information Networks [IJCAI2020]
• Heterogeneous Domain Adaptation via Soft Transfer Network [ACM MM2019]

Target-agnostic DA

Arxiv

• Compound Domain Adaptation in an Open World [8 Sep 2019]

Conference

• Domain Agnostic Learning with Disentangled Representations [ICML2019] [Pytorch]
• Blending-target Domain Adaptation by Adversarial Meta-Adaptation Networks [CVPR2019] [Pytorch]

Federated DA

Arxiv

• Federated Adversarial Domain Adaptation [5 Nov 2019]

Continuously Indexed DA

Conference

• Continuously Indexed Domain Adaptation [ICML 2020] [Pytorch] [Project Page] [Video]

Source Free DA

Conference

• Domain Adaptation with Adversarial Training on Penultimate Activations [AAAI2023] [Pytorch]
• Source-free Domain Adaptive Human Pose Estimation [ICCV2023][Pytorch]
• RAIN: RegulArization on Input and Network for Black-Box Domain Adaptation [IJCAI2023] [Pytorch]
• CoNMix for Source-free Single and Multi-target Domain Adaptation [WACV2022] [Pytorch]
• Source-free Video Domain Adaptation by Learning Temporal Consistency for Action Recognition [ECCV2022] [Pytorch] [Project]
• Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation [ECCV2022] [Project Page]
• Balancing Discriminability and Transferability for Source-Free Domain Adaptation [ICML2022] [Project Page]
• Source-free Domain Adaptation via Avatar Prototype Generation and Adaptation [IJCAI2021] [Pytorch]
• Confident Anchor-Induced Multi-Source Free Domain Adaptation [NeurIPS2021] [Pytorch]
• Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source Data [NeurIPS2021] [Pytorch]
• Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation [NeurIPS2021] [Pytorch]
• Unsupervised Domain Adaptation of Black-Box Source Models [BMVC2021][Pytorch]
• Generalize Then Adapt: Source-Free Domain Adaptive Semantic Segmentation [ICCV2021] [Project]
• Generalized Source-free Domain Adaptation [ICCV2021] [Pytorch]
• Adaptive Adversarial Network for Source-free Domain Adaptation [ICCV2021] [Pytorch]
• Visualizing Adapted Knowledge in Domain Transfer [CVPR2021] [Pytorch]
• Unsupervised Multi-source Domain Adaptation Without Access to Source Data [CVPR2021] [Pytorch]
• Source-Free Domain Adaptation for Semantic Segmentation [CVPR2021]
• Domain Impression: A Source Data Free Domain Adaptation Method [WACV2021] [Project]
• Model Adaptation: Unsupervised Domain Adaptation Without Source Data [CVPR2020]
• Universal Source-Free Domain Adaptation [CVPR2020] [Project]
• Towards Inheritable Models for Open-Set Domain Adaptation [CVPR2020] [Project]
• Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation [ICML2020] [Pytorch]

Arxiv

• Learning Invariant Representation with Consistency and Diversity for Semi-supervised Source Hypothesis Transfer[7 Jul 2021][Pytorch]
• Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer [14 Dec 2020] [Pytorch]

Active DA

Conference

• Local Context-Aware Active Domain Adaptation [ICCV2023] [Pytorch]
• Reducing Annotation Effort by Identifying and Labeling Contextually Diverse Classes for Semantic Segmentation Under Domain Shift [WACV2023]
• Towards Fewer Annotations: Active Learning via Region Impurity and Prediction Uncertainty for Domain Adaptive Semantic Segmentation [CVPR2022][Pytorch]
• Active Learning for Domain Adaptation: An Energy-based Approach [AAAI2022][Pytorch]
• Multi-Anchor Active Domain Adaptation for Semantic Segmentation [ICCV2021]
• Active Domain Adaptation via Clustering Uncertainty-Weighted Embeddings [ICCV2021]
• Active Universal Domain Adaptation [ICCV2021]
• S3VAADA: Submodular Subset Selection for Virtual Adversarial Active Domain Adaptation [ICCV2021]
• Transferable Query Selection for Active Domain Adaptation [CVPR2021]

Generalized Domain Adaptation

Conference

• Generalized Domain Adaptation [CVPR2021]

Model Selection

• Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation [ICLR2023ORAL] [Pytorch]
• The Balancing Principle for Parameter Choice in Distance-Regularized Domain Adaptation [NeurIPS2021] [Pytorch]
• Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation [ICML2019] [Pytorch]

Other Transfer Learning Paradigms

Domain Generalization

Conference

• Adapting to Distribution Shift by Visual Domain Prompt Generation [ICLR2024] [Pytorch]
• Test-Time Domain Adaptation by Learning Domain-Aware Batch Normalization [AAAI2024 (Oral)]
• A Dual-Augmentor Framework for Domain Generalization in 3D Human Pose Estimation [CVPR 2024] [Pytorch]
• Improving Single Domain-Generalized Object Detection: A Focus on Diversification and Alignment [CVPR 2024] [Pytorch]
• Generalization by Adaptation: Diffusion-Based Domain Extension for Domain-Generalized Semantic Segmentation [WACV 2024] [Pytorch]
• Topology-aware Robust Optimization for Out-of-Distribution Generalization [ICLR 2023] [Pytorch]
• A Re-Parameterized Vision Transformer (ReVT) for Domain-Generalized Semantic Segmentation [ICCV Workshop 2023] [Pytorch]
• Weight Averaging Improves Knowledge Distillation under Domain Shift [ICCV Workshop 2023] [Pytorch]
• Adaptive Texture Filtering for Single-Domain Generalized Segmentation [AAAI2023 oral] [Pytorch]
• PromptStyler: Prompt-driven Style Generation for Source-free Domain Generalization [ICCV2023] [Project]
• Sparse Mixture-of-Experts are Domain Generalizable Learners [ICLR2023(Oral)] [Pytorch]
• Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-Experts [NeruIPS2022] [Pytorch]
• Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentation [ECCV 2022] [Pytorch]
• Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification [CVPR 2021] [Pytorch]
• Domain Generalization via Inference-time Label-Preserving Target Projections [CVPR2021] [Pytorch]
• Domain Generalization via Entropy Regularization [NeurIPS2020] [Pytorch]
• Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization [NeurIPS2020]
• Learning to Learn with Variational Information Bottleneck for Domain Generalization [ECCV2020]
• Self-Challenging Improves Cross-Domain Generalization [ECCV2020] [Pytorch]
• Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization [ECCV2020] [Pytorch]
• Learning to Balance Specificity and Invariance for In and Out of Domain Generalization [ECCV2020] [Pytorch]
• Learning to Generate Novel Domains for Domain Generalization [ECCV2020]
• Learning to Optimize Domain Specific Normalization for Domain Generalization [ECCV2020]
• Towards Recognizing Unseen Categories in Unseen Domains [ECCV2020] [Pytorch]
• Efficient Domain Generalization via Common-Specific Low-Rank Decomposition [ICML2020] [Pytorch]
• Learning to Learn Single Domain Generalization [CVPR2020] [Pytorch]
• Generalized Convolutional Forest Networks for Domain Generalization and Visual Recognition [ICLR2020]
• Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation [ICLR2020]
• Domain Generalization Using a Mixture of Multiple Latent Domains [AAAI2020] [Pytorch]
• Deep Domain-Adversarial Image Generation for Domain Generalisation [Paper] [Pytorch]
• Domain Generalization via Model-Agnostic Learning of Semantic Features [NeurIPS2019] [Tensorflow]
• Episodic Training for Domain Generalization [ICCV2019 Oral] [Pytorch]](https://github.com/HAHA-DL/Episodic-DG)
• Feature-Critic Networks for Heterogeneous Domain Generalization [ICML2019] [Pytorch]
• Domain Generalization by Solving Jigsaw Puzzles [CVPR2019 Oral] [Pytorch]
• MetaReg: Towards Domain Generalization using Meta-Regularization [NIPS2018]
• Deep Domain Generalization via Conditional Invariant Adversarial Networks [ECCV2018]
• Domain Generalization with Adversarial Feature Learning [CVPR2018]

Journal

• Domain Generalization for Regression [IntellManuf2020]
• Correlation-aware Adversarial Domain Adaptation and Generalization [Pattern Recognition(2019)] [code]

Arxiv

• Adversarial Pyramid Network for Video Domain Generalization [8 Dec 2019]
• Towards Shape Biased Unsupervised Representation Learning for Domain Generalization [18 Sep 2019]
• A Generalization Error Bound for Multi-class Domain Generalization [24 May 2019]
• Adversarial Invariant Feature Learning with Accuracy Constraint for Domain Generalization [29 Apr 2019]
• Beyond Domain Adaptation: Unseen Domain Encapsulation via Universal Non-volume Preserving Models [9 Dec 2018]

Domain Randomization

Conference

• DeceptionNet: Network-Driven Domain Randomization [ICCV2019]
• Domain Randomization and Pyramid Consistency: Simulation-to-Real Generalization Without Accessing Target Domain Data [ICCV2019]

Transfer Metric Learning

• Transfer Metric Learning: Algorithms, Applications and Outlooks [arXiv]

Knowledge Transfer

Conference

• Attention Bridging Network for Knowledge Transfer [ICCV2019]
• Few-Shot Image Recognition with Knowledge Transfer [ICCV2019]

Others

Conference

• Learning Across Tasks and Domains [ICCV2019]
• UM-Adapt: Unsupervised Multi-Task Adaptation Using Adversarial Cross-Task Distillation [ICCV2019]
• Domain Agnostic Learning with Disentangled Representations [ICML2019]
• Unsupervised Open Domain Recognition by Semantic Discrepancy Minimization [CVPR2019] [Pytorch]

Arxiv

• GradMix: Multi-source Transfer across Domains and Tasks [[9 Feb 2020]](GradMix: Multi-source Transfer across Domains and Tasks)
• When Semi-Supervised Learning Meets Transfer Learning: Training Strategies, Models and Datasets [arXiv 13 Dec 2018]

Applications

Object Detection

Survey

• Unsupervised Domain Adaptation of Object Detectors: A Survey [Arxiv 27 May 2021]

Conference

• Improving Object Detection via Local-Global Contrastive Learning [BMVC2024] [Project]
• Supervision Interpolation via LossMix: Generalizing Mixup for Object Detection and Beyond [AAAI2024]
• Instance Relation Graph Guided Source-Free Domain Adaptive Object Detection [CVPR2023] [Project]
• Towards Online Domain Adaptive Object Detection [WACV2023] [[https://github.com/Vibashan/online-da]]
• Mixture of Teacher Experts for Source-Free Domain Adaptive Object Detection [ICIP2022]
• Towards Robust Adaptive Object Detection under Noisy Annotations [CVPR2022] [PyTorch]
• H²FA R-CNN: Holistic and Hierarchical Feature Alignment for Cross-Domain Weakly Supervised Object Detection [CVPR2022] [PyTorch] [PaddlePaddle]
• Cross-Domain Adaptive Teacher for Object Detection [CVPR2022] [Project] [PyTorch]
• Task-specific Inconsistency Alignment for Domain Adaptive Object Detection [CVPR2022] [PyTorch]
• SIGMA: Semantic-complete Graph Matching for Domain Adaptive Object Detection [CVPR2022] [PyTorch]
• Single-Domain Generalized Object Detection in Urban Scene via Cyclic-Disentangled Self-Distillation [CVPR2022]
• Target-Relevant Knowledge Preservation for Multi-Source Domain Adaptive Object Detection [CVPR2022]
• Cross Domain Object Detection by Target-Perceived Dual Branch Distillation [CVPR2022]
• Decoupled Adaptation for Cross-Domain Object Detection [ICLR2022] [PyTorch]
• SCAN: Cross Domain Object Detection with Semantic Conditioned Adaptation [AAAI2022] [PyTorch]
• SSAL: Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detection [NeurIPS2021] [Project]
• Multi-Source Domain Adaptation for Object Detection [ICCV2021]
• Knowledge Mining and Transferring for Domain Adaptive Object Detection [ICCV2021]
• Dual Bipartite Graph Learning: A General Approach for Domain Adaptive Object Detection [ICCV2021]
• Seeking Similarities over Differences: Similarity-based Domain Alignment for Adaptive Object Detection [ICCV2021]
• Informative and Consistent Correspondence Mining for Cross-Domain Weakly Supervised Object Detection [CVPR2021]
• MeGA-CDA: Memory Guided Attention for Category-Aware Unsupervised Domain Adaptive Object Detection [CVPR2021]
• SRDAN: Scale-aware and Range-aware Domain Adaptation Network for Cross-dataset 3D Object Detection [CVPR2021]
• I3Net: Implicit Instance-Invariant Network for Adapting One-Stage Object Detectors [CVPR2021]
• RPN Prototype Alignment for Domain Adaptive Object Detector [CVPR2021]
• ST3D: Self-training for Unsupervised Domain Adaptation on 3D ObjectDetection [CVPR2021]
• Domain-Specific Suppression for Adaptive Object Detection [CVPR2021]
• Unbiased Mean Teacher for Cross-Domain Object Detection [CVPR2021]
• YOLO in the Dark - Domain Adaptation Method for Merging Multiple Models [ECCV2020]
• Collaborative Training between Region Proposal Localization and Classification for Domain Adaptive Object Detection [ECCV2020]
• One-Shot Unsupervised Cross-Domain Detection [ECCV2020]
• Every Pixel Matters: Center-aware Feature Alignment for Domain Adaptive Object Detector [ECCV2020]
• Adapting Object Detectors with Conditional Domain Normalization [ECCV2020]
• Prior-based Domain Adaptive Object Detection for Hazy and Rainy Conditions [ECCV2020]
• Domain Adaptive Object Detection via Asymmetric Tri-way Faster-RCNN [ECCV2020]
• Cross-domain Object Detection through Coarse-to-Fine Feature Adaptation [CVPR2020]
• Harmonizing Transferability and Discriminability for Adapting Object Detectors [CVPR2020] [code]
• Exploring Categorical Regularization for Domain Adaptive Object Detection [CVPR2020] [code]
• Cross-domain Detection via Graph-induced Prototype Alignment [CVPR2020 Oral] [code]
• Multi-spectral Salient Object Detection by Adversarial Domain Adaptation [Paper]
• Deep Domain Adaptive Object Detection: a Survey [ICIP2020]
• Progressive Domain Adaptation for Object Detection [WACV]
• Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night [IJCNN2019 Oral] [Project]
• Self-Training and Adversarial Background Regularization for Unsupervised Domain Adaptive One-Stage Object Detection [ICCV2019 Oral]
• A Robust Learning Approach to Domain Adaptive Object Detection [ICCV2019] [code]
• Multi-adversarial Faster-RCNN for Unrestricted Object Detection [ICCV2019]
• Few-Shot Adaptive Faster R-CNN [CVPR2019]
• Exploring Object Relation in Mean Teacher for Cross-Domain Detection [CVPR2019]
• Adapting Object Detectors via Selective Cross-Domain Alignment [CVPR2019] [Pytorch]
• Automatic adaptation of object detectors to new domains using self-training [CVPR2019] [Project]
• Towards Universal Object Detection by Domain Attention [CVPR2019]
• Strong-Weak Distribution Alignment for Adaptive Object Detection [CVPR2019] [Pytorch]
• Diversify and Match: A Domain Adaptive Representation Learning Paradigm for Object Detection [CVPR2019] [Pytorch]
• Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation [CVPR2018]
• Domain Adaptive Faster R-CNN for Object Detection in the Wild [CVPR2018] [Caffe2] [Caffe] [Pytorch(under developing)]

Journal

• Cross-domain object detection using unsupervised image translation [ESWA]
• Pixel and feature level based domain adaptation for object detection in autonomous driving [Neurocomputing]

Arxiv

• See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain Adaptation [17 Nov 2021]
• Unsupervised Domain Adaptive Object Detection using Forward-Backward Cyclic Adaptation [3 Feb 2020]
• Prior-based Domain Adaptive Object Detection for Adverse Weather Conditions [29 Nov 2019]
• Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning [17 Nov 2019]
• Curriculum Self-Paced Learning for Cross-Domain Object Detection [15 Nov 2019]
• SCL: Towards Accurate Domain Adaptive Object Detection via Gradient Detach Based Stacked Complementary Losses [6 Nov 2019]

Semantic Segmentation

Conference

• PiPa: Pixel- and Patch-wise Self-supervised Learning for Domain Adaptative Semantic Segmentation [ACM MM2023] [Pytorch]
• Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions [WACV 2023] [Pytorch]
• Deliberated Domain Bridging for Domain Adaptive Semantic Segmentation [NeruIPS 2022] [Pytorch]
• DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentation [ECCV 2022] [Pytorch]
• HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation [ECCV 2022] [Pytorch]
• Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentation [ECCV 2022] [Pytorch]
• DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation [CVPR 2022] [Pytorch]
• Plugging Self-Supervised Monocular Depth into Unsupervised Domain Adaptation for Semantic Segmentation [WACV 2022]
• Shallow Features Guide Unsupervised Domain Adaptation for Semantic Segmentation at Class Boundaries [WACV 2022]
• Learning to Adapt via Latent Domains for Adaptive Semantic Segmentation [NeurIPS2021]
• Dual Path Learning for Domain Adaptation of Semantic Segmentation [ICCV2021]
• Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation [ICCV2021]
• Multi-Anchor Active Domain Adaptation for Semantic Segmentation [ICCV2021]
• LabOR: Labeling Only if Required for Domain Adaptive Semantic Segmentation [ICCV2021]
• Self-Mutating Network for Domain Adaptive Segmentation in Aerial Images [ICCV2021]
• Geometric Unsupervised Domain Adaptation for Semantic Segmentation [ICCV2021]
• Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation [ICCV2021]
• BAPA-Net: Boundary Adaptation and Prototype Alignment for Cross-Domain Semantic Segmentation [ICCV2021]
• BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentation [ICCV2021]
• Uncertainty-Aware Pseudo Label Refinery for Domain Adaptive Semantic Segmentation [ICCV2021]
• Domain Adaptive Semantic Segmentation With Self-Supervised Depth Estimation [ICCV2021]
• Generalize Then Adapt: Source-Free Domain Adaptive Semantic Segmentation [ICCV2021]
• DARCNN: Domain Adaptive Region-Based Convolutional Neural Network for Unsupervised Instance Segmentation in Biomedical Images [CVPR2021]
• DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation [CVPR2021]
• Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation [CVPR2021]
• Complete & Label: A Domain Adaptation Approach to Semantic Segmentation of LiDAR Point Clouds [CVPR2021]
• Cluster, Split, Fuse, and Update: Meta-Learning for Open Compound Domain Adaptive Semantic Segmentation [CVPR2021]
• PixMatch: Unsupervised Domain Adaptation via Pixelwise Consistency Training [CVPR2021] [Pytorch]
• Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation [CVPR2021] [Pytorch]
• Cross-View Regularization for Domain Adaptive Panoptic Segmentation [CVPR2021]
• Semi-supervised Domain Adaptation based on Dual-level Domain Mixing for Semantic Segmentation [CVPR2021]
• MetaCorrection: Domain-aware Meta Loss Correction for Unsupervised Domain Adaptation in Semantic Segmentation [CVPR2021]
• Coarse-to-Fine Domain Adaptive Semantic Segmentation with Photometric Alignment and Category-Center Regularization [CVPR2021]
• Multi-Source Domain Adaptation with Collaborative Learning for Semantic Segmentation [CVPR2021]
• Source-Free Domain Adaptation for Semantic Segmentation [CVPR2021]
• Instance Adaptive Self-Training for Unsupervised Domain Adaptation [ECCV 2020] [Pytorch]
• Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning [ICASSP 2020]
• Pixel-Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation [NeurlIPS 2020] [Pytorch]
• Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation [NeurIPS2020] [Pytorch]
• Semantically Adaptive Image-to-image Translation for Domain Adaptation of Semantic Segmentation [BMVC2020]
• Contextual-Relation Consistent Domain Adaptation for Semantic Segmentation [ECCV2020]
• Learning from Scale-Invariant Examples for Domain Adaptation in Semantic Segmentation [ECCV2020]
• Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation [ECCV2020]
• Unsupervised Domain Adaptation for Semantic Segmentation of NIR Images through Generative Latent Search [ECCV2020]
• Domain Adaptive Semantic Segmentation Using Weak Labels [ECCV2020]
• Content-Consistent Matching for Domain Adaptive Semantic Segmentation [ECCV2020] [PyTorch]
• Cross-Domain Semantic Segmentation via Domain-Invariant Interactive Relation Transfer [CVPR2020]
• Phase Consistent Ecological Domain Adaptation [CVPR2020] [Pytorch]
• FDA: Fourier Domain Adaptation for Semantic Segmentation [CVPR2020] [Pytorch]
• Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-weighting [CVPR2020]
• Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision [CVPR2020 Oral] [Pytorch]
• Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation [CVPR2020]
• Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation [CVPR2020] [Pytorch]
• xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation [CVPR2020] [Demo] [code]
• Unsupervised Scene Adaptation with Memory Regularization in vivo [IJCAI2020] [code]
• Joint Adversarial Learning for Domain Adaptation in Semantic Segmentation [AAAI2020]
• An Adversarial Perturbation Oriented Domain Adaptation Approach for Semantic Segmentation [AAAI2020]
• Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation [NeurIPS2019] [code]
• MLSL: Multi-Level Self-Supervised Learning for Domain Adaptation with Spatially Independent and Semantically Consistent Labeling [WACV2020]
• Domain Bridge for Unpaired Image-to-Image Translation and Unsupervised Domain Adaptation [WACV2020]
• Guided Curriculum Model Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation [ICCV2019]
• Constructing Self-motivated Pyramid Curriculums for Cross-Domain Semantic Segmentation: A Non-Adversarial Approach [ICCV2019] [Pytorch]
• SSF-DAN: Separated Semantic Feature Based Domain Adaptation Network for Semantic Segmentation [ICCV2019]
• Significance-aware Information Bottleneck for Domain Adaptive Semantic Segmentation [ICCV2019]
• Domain Adaptation for Semantic Segmentation with Maximum Squares Loss [ICCV2019] [Pytorch]
• Self-Ensembling with GAN-based Data Augmentation for Domain Adaptation in Semantic Segmentation [ICCV2019]
• DADA: Depth-aware Domain Adaptation in Semantic Segmentation [ICCV2019] [code]
• Domain Adaptation for Structured Output via Discriminative Patch Representations [ICCV2019 Oral] [Project]
• Not All Areas Are Equal: Transfer Learning for Semantic Segmentation via Hierarchical Region Selection [CVPR2019(Oral)]
• CrDoCo: Pixel-level Domain Transfer with Cross-Domain Consistency [CVPR2019] [Project] [Pytorch]
• Bidirectional Learning for Domain Adaptation of Semantic Segmentation [CVPR2019] [Pytorch]
• Learning Semantic Segmentation from Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach [CVPR2019]
• All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation [CVPR2019] [Pytorch]
• DLOW: Domain Flow for Adaptation and Generalization [CVPR2019 Oral]
• Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation [CVPR2019 Oral] [Pytorch]
• ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation [CVPR2019 Oral] [Pytorch]
• SPIGAN: Privileged Adversarial Learning from Simulation [ICLR2019]
• Penalizing Top Performers: Conservative Loss for Semantic Segmentation Adaptation [ECCV2018]
• Domain transfer through deep activation matching [ECCV2018]
• Unsupervised Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training [ECCV2018] [Pytorch]
• DCAN: Dual channel-wise alignment networks for unsupervised scene adaptation [ECCV2018]
• Fully convolutional adaptation networks for semantic segmentation [CVPR2018]
• Learning to Adapt Structured Output Space for Semantic Segmentation [CVPR2018] [Pytorch]
• Conditional Generative Adversarial Network for Structured Domain Adaptation [CVPR2018]
• Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation [CVPR2018] [Pytorch]
• Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes [ICCV2017] [Journal Version] [Keras]
• No more discrimination: Cross city adaptation of road scene segmenters [ICCV2017]

Journal

• SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation [TPAMI2023][arxiv version][Pytorch]
• Adaptive Boosting for Domain Adaptation: Towards Robust Predictions in Scene Segmentation [TIP2022][Pytorch]
• Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segmentation [IJCV2020][Pytorch]
• Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet [Neurocomputing 2021] [Pytorch]
• Affinity Space Adaptation for Semantic Segmentation Across Domains [TIP2020][Pytorch]
• Semantic-aware short path adversarial training for cross-domain semantic segmentation [Neurocomputing 2019]
• Weakly Supervised Adversarial Domain Adaptation for Semantic Segmentation in Urban Scenes [TIP]

Arxiv

• Class-Conditional Domain Adaptation on Semantic Segmentation [27 Nov 2019]
• Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation [2 Sep 2019]
• FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation [8 Dec 2016]
• BoMuDA: Boundless Multi-Source Domain Adaptive Segmentation in Unconstrained Environments [13 Oct 2020][Pytorch]
• SAfE: Self-Attention Based Unsupervised Road Safety Classification in Hazardous Environments [27 Nov 2020][Pytorch]
• Semantics-aware Multi-modal Domain Translation:From LiDAR Point Clouds to Panoramic Color Images [26 Jun 2021] [Pytorch]

Person Re-identification

Conference

• Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification [CVPR 2021] [Pytorch]
• Group-aware Label Transfer for Domain Adaptive Person Re-identification [CVPR2021]
• Unsupervised Domain Adaptation in the Dissimilarity Space for Person Re-identification [ECCV2020]
• Joint Visual and Temporal Consistency for Unsupervised Domain Adaptive Person Re-Identification [ECCV2020]
• Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification [ECV2020]
• Multiple Expert Brainstorming for Domain Adaptive Person Re-identification [ECCV2020]
• Deep Credible Metric Learning for Unsupervised Domain Adaptation Person Re-identification [ECCV2020]
• Unsupervised Domain Adaptation with Noise Resistible Mutual-Training for Person Re-identification [ECCV2020]
• Generalizing Person Re-Identification by Camera-Aware Invariance Learning and Cross-Domain Mixup [ECCV2020]
• AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identification [CVPR2020]
• Smoothing Adversarial Domain Attack and P-Memory Reconsolidation for Cross-Domain Person Re-Identification [CVPR2020]
• Cross-Modal Cross-Domain Moment Alignment Network for Person Search [CVPR2020]
• Online Joint Multi-Metric Adaptation From Frequent Sharing-Subset Mining for Person Re-Identification [CVPR2020]
• Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification [ICLR2020] [Pytorch]
• Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification [ICCV2019 Oral] [Pytorch]
• A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification [ICCV2019]
• Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification [CVPR2019] [Pytorch]
• Domain Adaptation through Synthesis for Unsupervised Person Re-identification [ECCV2018]
• Person Transfer GAN to Bridge Domain Gap for Person Re-Identification [CVPR2018]
• Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification [CVPR2018]

Arxiv

• Domain Adaptation for Semantic Segmentation via Patch-Wise Contrastive Learning [arXiv 22 Apr 2021]
• Structured Domain Adaptation for Unsupervised Person Re-identification [arXiv 14 Mar 2020]
• Domain Adaptive Attention Model for Unsupervised Cross-Domain Person Re-Identification [arXiv 25 May 2019]
• Camera Adversarial Transfer for Unsupervised Person Re-Identification [arXiv 2 Apr 2019]
• EANet: Enhancing Alignment for Cross-Domain Person Re-identification [arXiv 29 Dec 2018] [Pytorch]
• One Shot Domain Adaptation for Person Re-Identification [arXiv 26 Nov 2018]
• Similarity-preserving Image-image Domain Adaptation for Person Re-identification [arXiv 26 Nov 2018]

Sim-to-Real Transfer

Conference

• DIRL: Domain-Invariant Reperesentation Learning Approach for Sim-to-Real Transfer [CoRL2020] [Project]

Video Domain Adaptation

Conference

• Overcoming Label Noise for Source-free Unsupervised Video Domain Adaptation [[ICVGIP'22]] (https://dl.acm.org/doi/abs/10.1145/3571600.3571621) [Pytorch]](https://github.com/avijit9/CleanAdapt) [[Project]] (https://avijit9.github.io/CleanAdapt/) [[Extended Version]] (https://arxiv.org/abs/2311.18572)
• Source-free Video Domain Adaptation by Learning Temporal Consistency for Action Recognition [ECCV2022] [Pytorch] [Project]
• Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing [NeurIPS2021]
• Learning Cross-Modal Contrastive Features for Video Domain Adaptation [ICCV2021]
• Partial Video Domain Adaptation With Partial Adversarial Temporal Attentive Network [ICCV2021] [Pytorch]
• Domain Adaptive Video Segmentation via Temporal Consistency Regularization [ICCV2021]
• Shuffle and Attend: Video Domain Adaptation [ECCV2020]
• Transferring Cross-Domain Knowledge for Video Sign Language Recognition [CVPR2020]
• Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation [CVPR2020] [Pytorch]
• Transferring Cross-domain Knowledge for Video Sign Language Recognition [CVPR2020 Oral]
• Multi-Modal Domain Adaptation for Fine-Grained Action Recognition [CVPR2020 Oral]
• Adversarial Cross-Domain Action Recognition with Co-Attention [AAAI2020]
• Generative Adversarial Networks for Video-to-Video Domain Adaptation [Paper]
• Temporal Attentive Alignment for Large-Scale Video Domain Adaptation [ICCV2019 Oral] [Pytorch]
• Temporal Attentive Alignment for Video Domain Adaptation [CVPRW 2019] [Pytorch]

Arxiv

• Video Unsupervised Domain Adaptation with Deep Learning: A Comprehensive Survey [17 Nov 2022] [project]
• Unsupervised Video Domain Adaptation: A Disentanglement Perspective [15 Aug 2022] [Pyotrch] [Project] [Gradio Demo]
• Image to Video Domain Adaptation Using Web Supervision [5 Aug 2019]

Medical Related

Conference

• PopGenAdapt: Semi-Supervised Domain Adaptation for Genotype-to-Phenotype Prediction in Underrepresented Populations [PSB 2024]
• Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning [ICASSP 2020]
• What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation [Paper]
• Semantic-Transferable Weakly-Supervised Endoscopic Lesions Segmentation [ICCV2019]

Journal

• Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet [Neurocomputing 2021] [Pytorch]

Arxiv

• On-the-Fly Test-time Adaptation for Medical Image Segmentation [10 Mar 2022] [Pytorch]
• Target and task specific source-free domain adaptive image segmentation [10 Mar 2023] [Pytorch]
• Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation [arXiv 29 Aug 2019]
• Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation [arXiv on 24 Jan 2019]
• Unsupervised domain adaptation for medical imaging segmentation with self-ensembling [arXiv 14 Nov 2018]

Monocular Depth Estimation

• Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation [CVPR2019]
• Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer [CVPR2018]

3D

Conference

• SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation [ICCV2021]
• Sparse-to-Dense Feature Matching: Intra and Inter Domain Cross-Modal Learning in Domain Adaptation for 3D Semantic Segmentation [ICCV2021]
• Unsupervised Domain Adaptive 3D Detection With Multi-Level Consistency [ICCV2021]
• Domain-Adaptive Single-View 3D Reconstruction [ICCV2019]

Arxiv

• MS3D++: Ensemble of Experts for Multi-Source Unsupervised Domain Adaptation in 3D Object Detection [Arxiv 11 Aug 2023] [Pytorch]

Fine-Grained Domain

Conference

• Progressive Adversarial Networks for Fine-Grained Domain Adaptation [CVPR2020] [Pytorch]

LiDAR

Conference

• SALUDA: Surface-based Automotive Lidar Unsupervised Domain Adaptation [3DV 2024] [Pytorch]
• GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation [ECCV2022] [Pytorch]
• CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation [ECCV2022] [Pytorch]

ArXiv

• ConDA: Unsupervised Domain Adaptation for LiDAR Segmentation via Regularized Domain Concatenation [13 Mar 2022]

Remote Sensing

Journal

• Open-Set Black-Box Domain Adaptation for Remote Sensing Image Scene Classification [GRSL 2023]

Others

Conference

• RefRec: Pseudo-labels Refinement via Shape Reconstruction for Unsupervised 3D Domain Adaptation [3DV 2021 Oral]
• Unsupervised Domain Adaptation in LiDAR Semantic Segmentation with Self-Supervision and Gated Adapters [ICRA2022]
• RDA: Robust Domain Adaptation via Fourier Adversarial Attacking [ICCV2021]
• Geometry-Aware Self-Training for Unsupervised Domain Adaptation on Object Point Clouds [ICCV2021]
• Tune It the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density [ICCV2021]
• PIT: Position-Invariant Transform for Cross-FoV Domain Adaptation [ICCV2021]
• Self-Supervised Domain Adaptation for Forgery Localization of JPEG Compressed Images [ICCV2021]
• Unsupervised Real-World Super-Resolution: A Domain Adaptation Perspective [ICCV2021]
• Adversarial Robustness for Unsupervised Domain Adaptation [ICCV2021]
• Collaborative Optimization and Aggregation for Decentralized Domain Generalization and Adaptation [ICCV2021]
• Adaptive Cross-Modal Prototypes for Cross-Domain Visual-Language Retrieval [CVPR2021]
• Spatio-temporal Contrastive Domain Adaptation for Action Recognition [CVPR2021]
• Regressive Domain Adaptation for Unsupervised Keypoint Detection [CVPR2021]
• From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimation [CVPR2021] [code coming soon]
• Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark [ICCV Workshop 2021] [Pytorch]
• Adapting Neural Architectures Between Domains [NeurlPS 2020]
• Unsupervised Domain Attention Adaptation Network for Caricature Attribute Recognition [ECCV2020]
• A Broader Study of Cross-Domain Few-Shot Learning [ECCV2020]
• Label-Noise Robust Domain Adaptation [ICML2020]
• Unsupervised Domain Adaptation of a Pretrained Cross-Lingual Language Model [IJCAI2020]
• Domain Adaptation for Semantic Parsing [IJCAI2020]
• Bridging Cross-Tasks Gap for Cognitive Assessment via Fine-Grained Domain Adaptation [IJCAI2020]
• Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation [IJCAI2020]
• Weakly-Supervised Domain Adaptation via GAN and Mesh Model for Estimating 3D Hand Poses Interacting Objects [CVPR2020]
• One-Shot Domain Adaptation for Face Generation [CVPR2020]
• Learning Meta Face Recognition in Unseen Domains [CVPR2020 Oral] [code]
• Cross-Domain Document Object Detection: Benchmark Suite and Method [CVPR2020] [code]
• StereoGAN: Bridging Synthetic-to-Real Domain Gap by Joint Optimization of Domain Translation and Stereo Matching [CVPR2020]
• Domain Adaptation for Image Dehazing [CVPR2020]
• Probability Weighted Compact Feature for Domain Adaptive Retrieval [CVPR2020] [code]
• Disparity-Aware Domain Adaptation in Stereo Image Restoration [CVPR2020]
• Multi-Path Learning for Object Pose Estimation Across Domains [CVPR2020]
• Unsupervised Domain Adaptation for 3D Human Pose Estimation [ACM MM2019]
• PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation [NeurIPS 2019] [code]
• Deep Head Pose Estimation Using Synthetic Images and Partial Adversarial Domain Adaption for Continuous Label Spaces [ICCV2019]
• Cross-Domain Adaptation for Animal Pose Estimation [ICCV2019]
• GA-DAN: Geometry-Aware Domain Adaptation Network for Scene Text Detection and Recognition [ICCV2019]
• Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Pruning [IJCNN]
• Adversarial Adaptation of Scene Graph Models for Understanding Civic Issues [WWW2019]
• Cross-Dataset Adaptation for Visual Question Answering [CVPR2018]
• Cross-domain fault diagnosis through optimal transport for a CSTR process [DYCOPS2022] [Code]

Journal

• DASGIL: Domain Adaptation for Semantic and Geometric-Aware Image-Based Localization [TIP2020] [Pytorch]
• An Unsupervised Domain Adaptation Scheme for Single-Stage Artwork Recognition in Cultural Sites [Image and Vision Computing 2020] [Pytorch] [Project]
• Multi-source transfer learning of time series in cyclical manufacturing [JIntellManuf2020]
• Domain adaptation for regression under Beer-Lambert's law [KBS2020]

Arxiv

• Open-Ended Visual Question Answering by Multi-Modal Domain Adaptation [11 Nov 2019]
• DANE: Domain Adaptive Network Embedding [arXiv 3 Jun 2019]
• Active Adversarial Domain Adaptation [arXiv 16 Apr 2019]

Benchmarks

• Kurcuma: a kitchen utensil recognition collection for unsupervised domain adaptation [PAA2023] [Dataset]
• Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark [ICCV Workshop 2021] [Pytorch]
• LLVIP: A Visible-infrared Paired Dataset for Low-light Vision [ICCV Workshop 2021] [Pytorch]
• Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation [arXiv 26 Jun] [Project]
• Benchmarking Neural Network Robustness to Common Corruptions and Perturbations (ImageNet-C) [ICLR 2019] [PyTorch]

Library

• Transfer-Learning-Library
• deep-transfer-learning: a PyTorch library for deep transfer learning
• salad: a Semi-supervised Adaptive Learning Across Domains
• Dassl: a PyTorch toolbox for domain adaptation and semi-supervised learning
• joliGEN: an integrated framework for training custom generative AI image-to-image models

Lectures and Tutorials

• A Primer on Domain Adaptation [PDF]

Other Resources

• transferlearning