【Hackathon 7th PPSCI No.3】NO.3 DrivAerNet++ 论文复现 #1001
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LilaKen
changed the title
luotao1
assigned HydrogenSulfate, luotao1 and wangguan1995 and unassigned HydrogenSulfate
wangguan1995
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Nov 5, 2024
| 在复现模型时，选择了图卷积网络（RegDGCNN）和点云网络（PointNet）以捕获 DrivAer++ 数据集中的复杂几何关系。以下是选型考量： | ||
| - **网络模型选择**：RegDGCNN 用于捕捉几何结构的全局和局部依赖关系，PointNet 简化了对点云数据的处理流程。 | ||
| - **飞桨框架适配**：使用 Paconvert 进行代码转换，并对不兼容部分手动适配。 | ||
| - **数据加载和批处理**：由于 DrivAer++ 包含 8000 个样本，设计了高效的数据加载策略以支持模型的高效训练。 |
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具体数量7713个样本，这里的8000是参考DriveAerNet++中的表格，如果7713个样本数据没有问题的话，后续按照实际情况对文档进行修改。
| 本次任务旨在复现 DrivAerNet++ 的 RegDGCNN 和 PointNet 网络模型。在包含 8000 个样本的 DrivAer++ 数据集上实现高精度的气动性能预测，确保预测精度与论文中指标对齐，并满足代码审核要求。具体目标包括： | ||
| 1. 复现 DrivAer++ 数据集上的 RegDGCNN 和 PointNet 模型。 | ||
| 2. 确保飞桨版本代码的精度达到与原论文一致的水平。 | ||
| 3. 编写完整的设计文档，满足代码审核和发布的规范要求。 |
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好的，后期会进行详细，目前提交一版RFC方便联系导师后续工作开展。
| |-----------|------------|------------|---------------|--------|------| | ||
| | RegDGCNN | 14.2 | 9.31 | 12.79 | 0.641 | 原论文 | | ||
| | PointNet | 14.9 | 9.6 | 12.45 | 0.643 | 原论文 | | ||
| | RegDGCNN | 待测试 | 待测试 | 待测试 | 待测试 | Pytorch复现 | |
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