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Long Range Pooling for 3D Large-Scale Scene Understanding
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add the LRP module after each stage | VMNet U-Net · ScanNet v2 val | mIoU (%): 71.2 -> 75.0 | Helped |
| Add max pooling without dilation or receptive-field selection (ablation) | VMNet U-Net · ScanNet v2 val | mIoU (%): 71.2 -> 72.6 | Helped |
| Add dilation to max pooling without receptive-field selection (ablation) | VMNet U-Net · ScanNet v2 val | mIoU (%): 72.6 -> 73.7 | Helped |
| Add receptive-field selection to max pooling without dilation (ablation) | VMNet U-Net · ScanNet v2 val | mIoU (%): 72.6 -> 73.1 | Helped |
| Use both dilated max pooling and receptive-field selection (ablation) | VMNet U-Net · ScanNet v2 val | mIoU (%): 73.7 -> 75.0 | Helped |
| Place LRP before stages rather than after them (ablation) | VMNet U-Net · ScanNet v2 val | mIoU (%): 75.0 -> 74.0 | Hurt |
| Place LRP in the middle of stages rather than after them (ablation) | VMNet U-Net · ScanNet v2 val | mIoU (%): 75.0 -> 73.4 | Hurt |
| Place LRP in a parallel branch rather than after stages (ablation) | VMNet U-Net · ScanNet v2 val | mIoU (%): 75.0 -> 73.1 | Hurt |
| Expand the max-pooling receptive-field range from ×3 to ×27 (ablation) | LRP · ScanNet v2 val | mIoU (%): 72.7 -> 73.9 | Helped |
| Use max pooling at ×3, ×9 and ×27 instead of ×27 only (ablation) | LRP · ScanNet v2 val | mIoU (%): 73.9 -> 75.0 | Helped |
| Replace dilation max pooling with dilation average pooling across the tested ranges (ablation) | LRP · ScanNet v2 val | mIoU (%): 75.0 -> 73.9 | Hurt |
| Replace dilation max pooling with dilation convolution across the tested ranges (ablation) | LRP · ScanNet v2 val | mIoU (%): 75.0 -> 73.8 | Hurt |
Closest papers by meaning
- LSK3DNet: Towards Effective and Efficient 3D Perception with Large Sparse Kernels (CVPR 2024 · similarity 0.85)
- A General Protocol to Probe Large Vision Models for 3D Physical Understanding (NeurIPS 2024 · similarity 0.85)
- Large Spatial Model: End-to-end Unposed Images to Semantic 3D (NeurIPS 2024 · similarity 0.84)
- CAM Back Again: Large Kernel CNNs from a Weakly Supervised Object Localization Perspective (CVPR 2024 · similarity 0.84)
- Beyond Skip Connection: Pooling and Unpooling Design for Elimination Singularities (AAAI 2025 · similarity 0.84)
- DL3DV-10K: A Large-Scale Scene Dataset for Deep Learning-based 3D Vision (CVPR 2024 · similarity 0.84)
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