Pointnet2_PyTorch
Pointnet_Pointnet2_pytorch
Pointnet2_PyTorch | Pointnet_Pointnet2_pytorch | |
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1 | 3 | |
1,399 | 3,219 | |
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0.0 | 0.0 | |
2 months ago | 15 days ago | |
Python | Python | |
The Unlicense | MIT License |
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Pointnet2_PyTorch
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[D] Implementing custom functions in pytorch e.g. feature propagation (PointNet++)
Apologies if this isn't the right place to ask. But I'm currently studying point cloud-based networks like pointcloud++, and all the related 3d object detection networks like pointpillars, voxelnet, etc. While I (think) understand the algorithms like feature propagation in pointnet++. I'm having trouble understanding how would one implement them. Or Where could I learn about writing operations in cuda and making sure they are compatible with backprop?
Pointnet_Pointnet2_pytorch
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Help me understand how to use this PointNet implementation (pytorch, point cloud classification)
here is a sample from one of these log files
I am trying to use this implementation of PointNet (GitHub repo)
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Are the New M1 Macbooks Any Good for Deep Learning? Let’s Find Out
Here you go: https://github.com/yanx27/Pointnet_Pointnet2_pytorch - no need for any custom cuda code.
Note the cuda kernels in the original repo were added in August 2017. It might have been the case at the time they needed them, but again, if you need to do something like that today, you're probably an outlier. Modern DL library have a pretty vast assortment of ops. There have been a few cases in the last couple of years when I thought I'd need write a custom op in cuda (e.g. np.unpackbits) but every time I found a way to implement it with native Pytorch ops.
If you're doing DL/CV research, can you give an example from your own work where you really need to run custom cuda code today?
What are some alternatives?
mdx-net - KUIELAB-MDX-Net got the 2nd place on the Leaderboard A and the 3rd place on the Leaderboard B in the MDX-Challenge ISMIR 2021
tensorflow_macos - TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute framework.
SimpleView - Official Code for ICML 2021 paper "Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline"
pointnet2 - PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
Pix2Vox - The official implementation of "Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images". (Xie et al., ICCV 2019)
RAFT
ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
mmrazor - OpenMMLab Model Compression Toolbox and Benchmark.
DeepViewAgg - [CVPR'22 Best Paper Finalist] Official PyTorch implementation of the method presented in "Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation"
pointnet - PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation