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metafile.yml
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Collections:
- Name: SPVCNN
Metadata:
Training Techniques:
- AdamW
Architecture:
- SPVCNN
Paper:
URL: https://arxiv.org/abs/2007.16100
Title: 'Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution'
README: configs/spvcnn/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection3d/blob/1.1/mmdet3d/models/backbones/spvcnn_backone.py#L22
Version: v1.1.0
Models:
- Name: spvcnn_w16_8xb2-amp-15e_semantickitti
In Collection: SPVCNN
Config: configs/spvcnn/spvcnn_w16_8xb2-amp-15e_semantickitti.py
Metadata:
Training Data: SemanticKITTI
Training Memory (GB): 3.9
Training Resources: 8x A100 GPUs
Results:
- Task: 3D Semantic Segmentation
Dataset: SemanticKITTI
Metrics:
mIOU: 61.7
Weights: https://download.openmmlab.com/mmdetection3d/v1.1.0_models/spvcnn/spvcnn_w16_8xb2-15e_semantickitti/spvcnn_w16_8xb2-15e_semantickitti_20230321_011645-a2734d85.pth
- Name: spvcnn_w20_8xb2-amp-15e_semantickitti
In Collection: SPVCNN
Config: configs/spvcnn/spvcnn_w20_8xb2-amp-15e_semantickitti.py
Metadata:
Training Data: SemanticKITTI
Training Memory (GB): 4.2
Training Resources: 8x A100 GPUs
Results:
- Task: 3D Semantic Segmentation
Dataset: SemanticKITTI
Metrics:
mIOU: 62.9
Weights: https://download.openmmlab.com/mmdetection3d/v1.1.0_models/spvcnn/spvcnn_w20_8xb2-15e_semantickitti/spvcnn_w20_8xb2-15e_semantickitti_20230321_011649-519e7eff.pth
- Name: spvcnn_w32_8xb2-amp-15e_semantickitti
In Collection: SPVCNN
Config: configs/spvcnn/spvcnn_w32_8xb2-amp-15e_semantickitti.py
Metadata:
Training Data: SemanticKITTI
Training Memory (GB): 5.4
Training Resources: 8x A100 GPUs
Results:
- Task: 3D Semantic Segmentation
Dataset: SemanticKITTI
Metrics:
mIOU: 64.3
Weights: https://download.openmmlab.com/mmdetection3d/v1.1.0_models/spvcnn/spvcnn_w32_8xb2-15e_semantickitti/spvcnn_w32_8xb2-15e_semantickitti_20230308_113324-f7c0c5b4.pth
- Name: spvcnn_w32_8xb2-amp-laser-polar-mix-3x_semantickitti
In Collection: SPVCNN
Config: configs/spvcnn/spvcnn_w32_8xb2-amp-laser-polar-mix-3x_semantickitti.py
Metadata:
Training Data: SemanticKITTI
Training Memory (GB): 7.2
Training Resources: 8x A100 GPUs
Results:
- Task: 3D Semantic Segmentation
Dataset: SemanticKITTI
Metrics:
mIOU: 64.3
Weights: https://download.openmmlab.com/mmdetection3d/v1.1.0_models/spvcnn/spvcnn_w32_8xb2-amp-laser-polar-mix-3x_semantickitti_20230425_125908-d68a68b7.pth