dvlab-research / VoxelNeXt

VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Tracking (CVPR 2023)
https://arxiv.org/abs/2303.11301
Apache License 2.0
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Question about cfgs file #31

Open Seong-min-Park opened 1 year ago

Seong-min-Park commented 1 year ago

Thank you for the excellent research. I have a question about the cfgs file provided in the code. When I tried to reproduce using the cbgs_voxel0075_voxelnext.yaml, I noticed that the FLOPs calculation shows a model with a spatial pruning ratio of 0 (83.8 GFLOPs), as seen in Table 3. Is there a model config file available with a spatial pruning ratio of 0.5, or is there a way to separately configure the pruning ratio?

yukang2017 commented 1 year ago

You can change the backbone name to be "VoxelResBackBone8xVoxelNeXtSPS" in the config file.

Seong-min-Park commented 1 year ago

Thank you for your response. I have an additional question. To obtain a model with 33.6 GFLOPs, similar to the result with a ratio of 0.5 in table3, should I set the pruning ratio of the SPS module to 0.5? (When I tried reproducing it, setting the pruning ratio of SPS module to 0.5 didn't result in the expected reduction in computational cost.)

yukang2017 commented 1 year ago

Yes. 0.5 is the right setting. Would you please show me how you calculate FLOPs?

I used the method provided in this work. https://github.com/CVMI-Lab/SparseKD

Seong-min-Park commented 1 year ago

I measured the computation cost of the model by directly calculating the number of active points in each layer using input.features.shape[0] in the conv forward of the spconv library. The flops of each layer were computed as _*input_channel output_channel kernel_size^dim #activepoints**, and then I summed up the flops of all layers.