[Feature] Adding PWC metafile (#485)

* [Feature] Adding PWC metafile

* fix url in nuimages

* removing inaccurate training time

* refine pwc index

* refine training resources

* removing empty metric of metafile in regnet

* removing 'Focal_Loss' and 'SECOND' from Architecture

configs/3dssd/metafile.yml

+Collections:
+  - Name: 3DSSD
+    Metadata:
+      Training Data: KITTI
+      Training Techniques:
+        - AdamW
+      Training Resources: 4x TITAN X
+      Architecture:
+        - PointNet++
+    Paper: https://arxiv.org/abs/2002.10187
+    README: configs/3dssd/README.md
+
+Models:
+  - Name: 3dssd_kitti-3d-car
+    In Collection: 3DSSD
+    Config: configs/3dssd/3dssd_kitti-3d-car.py
+    Metadata:
+      Training Memory (GB): 4.7
+    Results:
+      - Task: 3D Object Detection
+        Dataset: KITTI
+        Metrics:
+          mAP: 78.39
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/3dssd/3dssd_kitti-3d-car_20210324_122002-07e9a19b.pth

configs/centerpoint/metafile.yml

+Collections:
+  - Name: CenterPoint
+    Metadata:
+      Training Data: nuScenes
+      Training Techniques:
+        - AdamW
+      Training Resources: 8x V100 GPUs
+      Architecture:
+        - Hard Voxelization
+    Paper: https://arxiv.org/abs/2006.11275
+    README: configs/centerpoint/README.md
+
+Models:
+  - Name: centerpoint_01voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus
+    In Collection: CenterPoint
+    Config: configs/centerpoint/centerpoint_01voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus.py
+    Metadata:
+      Training Memory (GB): 4.9
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 56.19
+          NDS: 64.43
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/centerpoint/centerpoint_01voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus/centerpoint_01voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus_20201001_135205-5db91e00.pth
+
+  - Name: centerpoint_01voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus
+    In Collection: CenterPoint
+    Config: configs/centerpoint/centerpoint_01voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py
+    Metadata:
+      Training Memory (GB): 5.2
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 56.34
+          NDS: 64.81
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/centerpoint/centerpoint_01voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus/centerpoint_01voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus_20201004_075317-26d8176c.pth
+
+  - Name: centerpoint_0075voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus
+    In Collection: CenterPoint
+    Config: configs/centerpoint/centerpoint_0075voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus.py
+    Metadata:
+      Training Memory (GB): 7.8
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 57.34
+          NDS: 65.23
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/centerpoint/centerpoint_0075voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus/centerpoint_0075voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus_20200925_230905-358fbe3b.pth
+
+  - Name: centerpoint_0075voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus
+    In Collection: CenterPoint
+    Config: configs/centerpoint/centerpoint_0075voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus.py
+    Metadata:
+      Training Memory (GB): 8.5
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 57.27
+          NDS: 65.58
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/centerpoint/centerpoint_0075voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus/centerpoint_0075voxel_second_secfpn_dcn_circlenms_4x8_cyclic_20e_nus_20200930_201619-67c8496f.pth
+
+  - Name: centerpoint_02pillar_second_secfpn_circlenms_4x8_cyclic_20e_nus
+    In Collection: CenterPoint
+    Config: configs/centerpoint/centerpoint_02pillar_second_secfpn_circlenms_4x8_cyclic_20e_nus.py
+    Metadata:
+      Training Memory (GB): 4.4
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 49.07
+          NDS: 59.66
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/centerpoint/centerpoint_01voxel_second_secfpn_circlenms_4x8_cyclic_20e_nus/centerpoint_02pillar_second_secfpn_circlenms_4x8_cyclic_20e_nus_20201004_170716-a134a233.pth
+
+  - Name: centerpoint_02pillar_second_secfpn_dcn_4x8_cyclic_20e_nus
+    In Collection: CenterPoint
+    Config: configs/centerpoint/centerpoint_02pillar_second_secfpn_dcn_4x8_cyclic_20e_nus.py
+    Metadata:
+      Training Memory (GB): 4.6
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 48.8
+          NDS: 59.67
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/centerpoint/centerpoint_02pillar_second_secfpn_dcn_4x8_cyclic_20e_nus/centerpoint_02pillar_second_secfpn_dcn_4x8_cyclic_20e_nus_20200930_103722-3bb135f2.pth

configs/dynamic_voxelization/metafile.yml

+Collections:
+  - Name: Dynamic Voxelization
+    Metadata:
+      Training Data: KITTI
+      Training Techniques:
+        - AdamW
+      Training Resources: 8x V100 GPUs
+      Architecture:
+        - Dynamic Voxelization
+    Paper: https://arxiv.org/abs/1910.06528
+    README: configs/dynamic_voxelization/README.md
+
+Models:
+  - Name: dv_second_secfpn_6x8_80e_kitti-3d-car
+    In Collection: Dynamic Voxelization
+    Config: configs/dynamic_voxelization/dv_second_secfpn_6x8_80e_kitti-3d-car.py
+    Metadata:
+      Training Memory (GB): 5.5
+    Results:
+      - Task: 3D Object Detection
+        Dataset: KITTI
+        Metrics:
+          mAP: 78.83
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/dynamic_voxelization/dv_second_secfpn_6x8_80e_kitti-3d-car/dv_second_secfpn_6x8_80e_kitti-3d-car_20200620_235228-ac2c1c0c.pth
+
+  - Name: dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class
+    In Collection: Dynamic Voxelization
+    Config: configs/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class.py
+    Metadata:
+      Training Memory (GB): 5.5
+    Results:
+      - Task: 3D Object Detection
+        Dataset: KITTI
+        Metrics:
+          mAP: 65.10
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/dynamic_voxelization/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class/dv_second_secfpn_2x8_cosine_80e_kitti-3d-3class_20200620_231010-6aa607d3.pth
+
+  - Name: dv_pointpillars_secfpn_6x8_160e_kitti-3d-car
+    In Collection: Dynamic Voxelization
+    Config: configs/dynamic_voxelization/dv_pointpillars_secfpn_6x8_160e_kitti-3d-car.py
+    Metadata:
+      Training Memory (GB): 4.7
+    Results:
+      - Task: 3D Object Detection
+        Dataset: KITTI
+        Metrics:
+          mAP: 77.76
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/dynamic_voxelization/dv_pointpillars_secfpn_6x8_160e_kitti-3d-car/dv_pointpillars_secfpn_6x8_160e_kitti-3d-car_20200620_230844-ee7b75c9.pth

configs/fp16/metafile.yml

+Collections:
+  - Name: FP16
+    Metadata:
+      Training Techniques:
+        - AdamW
+        - Mixed Precision Training
+      Training Resources: 8x TITAN Xp
+      Architecture:
+        - Hard Voxelization
+    Paper:
+      - https://www.mdpi.com/1424-8220/18/10/3337
+      - https://arxiv.org/abs/1812.05784
+    README: configs/fp16/README.md
+
+Models:
+  - Name: hv_second_secfpn_fp16_6x8_80e_kitti-3d-car
+    In Collection: FP16
+    Config: configs/fp16/hv_second_secfpn_fp16_6x8_80e_kitti-3d-car.py
+    Metadata:
+      Training Data: KITTI
+      Training Memory (GB): 2.9
+    Results:
+      - Task: 3D Object Detection
+        Dataset: KITTI
+        Metrics:
+          FP16 mAP: 78.72
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fp16/hv_second_secfpn_fp16_6x8_80e_kitti-3d-car/hv_second_secfpn_fp16_6x8_80e_kitti-3d-car_20200924_211301-1f5ad833.pth
+
+  - Name: hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class
+    In Collection: FP16
+    Config: configs/fp16/hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class.py
+    Metadata:
+      Training Data: KITTI
+      Training Memory (GB): 2.9
+    Results:
+      - Task: 3D Object Detection
+        Dataset: KITTI
+        Metrics:
+          FP16 mAP: 67.4
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fp16/hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class/hv_second_secfpn_fp16_6x8_80e_kitti-3d-3class_20200925_110059-05f67bdf.pth
+
+  - Name: hv_pointpillars_secfpn_sbn-all_fp16_2x8_2x_nus-3d
+    In Collection: FP16
+    Config: configs/fp16/hv_pointpillars_secfpn_sbn-all_fp16_2x8_2x_nus-3d.py
+    Metadata:
+      Training Data: nuScenes
+      Training Memory (GB): 8.37
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          FP16 mAP: 35.19
+          FP16 NDS: 50.27
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fp16/hv_pointpillars_secfpn_sbn-all_fp16_2x8_2x_nus-3d/hv_pointpillars_secfpn_sbn-all_fp16_2x8_2x_nus-3d_20201020_222626-c3f0483e.pth
+
+  - Name: hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d
+    In Collection: FP16
+    Config: configs/fp16/hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d.py
+    Metadata:
+      Training Data: nuScenes
+      Training Memory (GB): 8.40
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          FP16 mAP: 39.26
+          FP16 NDS: 53.26
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/fp16/hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d/hv_pointpillars_fpn_sbn-all_fp16_2x8_2x_nus-3d_20201021_120719-269f9dd6.pth

configs/free_anchor/metafile.yml

+Collections:
+  - Name: FreeAnchor
+    Metadata:
+      Training Data: nuScenes
+      Training Techniques:
+        - AdamW
+      Training Resources: 8x V100 GPUs
+      Architecture:
+        - Hard Voxelization
+        - Free Anchor
+    Paper: https://arxiv.org/abs/1909.02466
+    README: configs/free_anchor/README.md
+
+Models:
+  - Name: hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d
+    In Collection: FreeAnchor
+    Config: free_anchor/hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py
+    Metadata:
+      Training Memory (GB): 16.2
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 43.7
+          NDS: 55.3
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/free_anchor/hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d/hv_pointpillars_fpn_sbn-all_free-anchor_4x8_2x_nus-3d_20200628_210537-09d359fc.pth
+
+  - Name: hv_pointpillars_regnet-400mf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d
+    In Collection: FreeAnchor
+    Config: configs/free_anchor/hv_pointpillars_regnet-400mf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py
+    Metadata:
+      Training Memory (GB): 17.7
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 47.9
+          NDS: 58.6
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/free_anchor/hv_pointpillars_regnet-400mf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d/hv_pointpillars_regnet-400mf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d_20200629_050311-a334765d.pth
+
+  - Name: hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d
+    In Collection: FreeAnchor
+    Config: configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py
+    Metadata:
+      Training Memory (GB): 24.3
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 51.2
+          NDS: 60.8
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d_20200629_105446-6ffa59cb.pth
+
+  - Name: hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d
+    In Collection: FreeAnchor
+    Config: configs/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py
+    Metadata:
+      Training Memory (GB): 24.3
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 53.0
+          NDS: 62.2
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/free_anchor/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d_20200701_201531-036f7de3.pth
+
+  - Name: hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d
+    In Collection: FreeAnchor
+    Config: configs/free_anchor/hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d.py
+    Metadata:
+      Training Memory (GB): 29.5
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 52.2
+          NDS: 62.0
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/free_anchor/hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d/hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_4x8_2x_nus-3d_20200629_055854-658125b0.pth
+
+  - Name: hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d
+    In Collection: FreeAnchor
+    Config: configs/free_anchor/hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d.py
+    Metadata:
+      Training Memory (GB): 29.5
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 55.09
+          NDS: 63.5
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/free_anchor/hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d/hv_pointpillars_regnet-3.2gf_fpn_sbn-all_free-anchor_strong-aug_4x8_3x_nus-3d_20200629_181452-297fdc66.pth

configs/h3dnet/metafile.yml

+Collections:
+  - Name: H3DNet
+    Metadata:
+      Training Data: ScanNet
+      Training Techniques:
+        - AdamW
+      Training Resources: 8x GeForce GTX 1080 Ti
+      Architecture:
+    Paper: https://arxiv.org/abs/2006.05682
+    README: configs/h3dnet/README.md
+
+Models:
+  - Name: h3dnet_3x8_scannet-3d-18class
+    In Collection: H3DNet
+    Config: configs/h3dnet/h3dnet_3x8_scannet-3d-18class.py
+    Metadata:
+      Training Memory (GB): 7.9
+    Results:
+      - Task: 3D Object Detection
+        Dataset: ScanNet
+        Metrics:
+          AP@0.25: 66.43
+          AP@0.5: 48.01
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/h3dnet/h3dnet_scannet-3d-18class/h3dnet_scannet-3d-18class_20200830_000136-02e36246.pth

configs/imvotenet/metafile.yml

+Collections:
+  - Name: ImVoteNet
+    Metadata:
+      Training Data: SUNRGBD
+      Training Techniques:
+        - AdamW
+      Training Resources: 8x TITAN Xp
+      Architecture:
+        - Faster R-CNN
+        - VoteNet
+        - Feature Pyramid Network
+    Paper: https://arxiv.org/abs/2001.10692
+    README: configs/imvotenet/README.md
+
+Models:
+  - Name: imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class
+    In Collection: ImVoteNet
+    Config: configs/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class.py
+    Metadata:
+      Training Memory (GB): 2.1
+    Results:
+      - Task: Object Detection
+        Dataset: SUNRGBD-2D
+        Metrics:
+          AP@0.5: 62.70
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/imvotenet/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class/imvotenet_faster_rcnn_r50_fpn_2x4_sunrgbd-3d-10class_20210323_173222-cad62aeb.pth
+
+  - Name: imvotenet_stage2_16x8_sunrgbd-3d-10class
+    In Collection: ImVoteNet
+    Config: configs/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class.py
+    Metadata:
+      Training Memory (GB): 9.4
+    Results:
+      - Task: 3D Object Detection
+        Dataset: SUNRGBD-3D
+        Metrics:
+          AP@0.25: 64.04
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class/imvotenet_stage2_16x8_sunrgbd-3d-10class_20210323_184021-d44dcb66.pth

configs/mvxnet/metafile.yml

+Collections:
+  - Name: MVX-Net
+    Metadata:
+      Training Data: KITTI
+      Training Techniques:
+        - AdamW
+      Training Resources: 8x V100 GPUs
+      Architecture:
+        - Feature Pyramid Network
+        - Dynamic Voxelization
+    Paper: https://arxiv.org/abs/1904.01649
+    README: configs/mvxnet/README.md
+
+Models:
+  - Name: dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class
+    In Collection: MVX-Net
+    Config: configs/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class.py
+    Metadata:
+      Training Memory (GB): 6.7
+    Results:
+      - Task: 3D Object Detection
+        Dataset: KITTI
+        Metrics:
+          mAP: 63.0
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/mvxnet/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class/dv_mvx-fpn_second_secfpn_adamw_2x8_80e_kitti-3d-3class_20200621_003904-10140f2d.pth

configs/nuimages/README.md

@@ -37,7 +37,7 @@ We report Mask R-CNN and Cascade Mask R-CNN results on nuimages.
 | Mask R-CNN| [R-50](./mask_rcnn_r50_fpn_coco-2x_1x_nuim.py) |IN+COCO-2x|1x|7.4|49.7|40.5|[model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_coco-2x_1x_nuim/mask_rcnn_r50_fpn_coco-2x_1x_nuim_20201008_195238-b1742a60.pth) | [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_coco-2x_1x_nuim/mask_rcnn_r50_fpn_coco-2x_1x_nuim_20201008_195238.log.json)|
 | Mask R-CNN| [R-50-CAFFE](./mask_rcnn_r50_caffe_fpn_1x_nuim.py) |IN|1x|7.0|47.7|38.2|[model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_1x_nuim/) | [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_1x_nuim/)|
 | Mask R-CNN| [R-50-CAFFE](./mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim.py) |IN+COCO-3x|1x|7.0|49.9|40.8|[model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim/mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim_20201008_195305-661a992e.pth) | [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim/mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim_20201008_195305.log.json)|
-| Mask R-CNN| [R-50-CAFFE](./mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim.py) |IN+COCO-3x|20e|7.0|50.6|41.3|[model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim_20201009_125002-5529442c.pth) | [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim_20201009_125002.log.json)|
+| Mask R-CNN| [R-50-CAFFE](./mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim.py) |IN+COCO-3x|20e|7.0|50.6|41.3|[model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim_20201009_125002-5529442c.pth) | [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim_20201009_125002.log.json)|
 | Mask R-CNN| [R-101](./mask_rcnn_r101_fpn_1x_nuim.py) |IN|1x|10.9|48.9|39.1|[model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r101_fpn_1x_nuim/mask_rcnn_r101_fpn_1x_nuim_20201024_134803-65c7623a.pth) | [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r101_fpn_1x_nuim/mask_rcnn_r101_fpn_1x_nuim_20201024_134803.log.json)|
 | Mask R-CNN| [X-101_32x4d](./mask_rcnn_x101_32x4d_fpn_1x_nuim.py) |IN|1x|13.3|50.4|40.5|[model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_x101_32x4d_fpn_1x_nuim/mask_rcnn_x101_32x4d_fpn_1x_nuim_20201024_135741-b699ab37.pth) | [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_x101_32x4d_fpn_1x_nuim/mask_rcnn_x101_32x4d_fpn_1x_nuim_20201024_135741.log.json)|
 | Cascade Mask R-CNN| [R-50](./cascade_mask_rcnn_r50_fpn_1x_nuim.py) |IN|1x|8.9|50.8|40.4|[model](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r50_fpn_1x_nuim/cascade_mask_rcnn_r50_fpn_1x_nuim_20201008_195342-1147c036.pth) | [log](https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r50_fpn_1x_nuim/cascade_mask_rcnn_r50_fpn_1x_nuim_20201008_195342.log.json)|

configs/nuimages/metafile.yml

+Collections:
+  - Name: Mask R-CNN
+    Metadata:
+      Training Data: nuImages
+      Training Techniques:
+        - SGD with Momentum
+      Architecture:
+        - RoI Align
+        - RPN
+    Paper:
+      - https://arxiv.org/abs/1703.06870
+      - https://arxiv.org/abs/1712.00726v1
+    README: configs/nuimages/README.md
+
+Models:
+  - Name: mask_rcnn_r50_fpn_1x_nuim
+    In Collection: Mask R-CNN
+    Config: configs/nuimages/mask_rcnn_r50_fpn_1x_nuim.py
+    Metadata:
+      Training Memory (GB): 7.4
+      Training Resources: 8x TITAN Xp
+    Results:
+      - Task: Object Detection
+        Dataset: nuImages
+        Metrics:
+          Box AP: 47.8
+      - Task: Instance Segmentation
+        Dataset: nuImages
+        Metrics:
+          Mask AP: 38.4
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_1x_nuim/mask_rcnn_r50_fpn_1x_nuim_20201008_195238-e99f5182.pth
+
+  - Name: mask_rcnn_r50_fpn_coco-2x_1x_nuim
+    In Collection: Mask R-CNN
+    Config: configs/nuimages/mask_rcnn_r50_fpn_coco-2x_1x_nuim.py
+    Metadata:
+      Training Memory (GB): 7.4
+      Training Resources: 8x TITAN Xp
+    Results:
+      - Task: Object Detection
+        Dataset: nuImages
+        Metrics:
+          Box AP: 49.7
+      - Task: Instance Segmentation
+        Dataset: nuImages
+        Metrics:
+          Mask AP: 40.5
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_fpn_coco-2x_1x_nuim/mask_rcnn_r50_fpn_coco-2x_1x_nuim_20201008_195238-b1742a60.pth
+
+  - Name: mask_rcnn_r50_caffe_fpn_1x_nuim
+    In Collection: Mask R-CNN
+    Config: configs/nuimages/mask_rcnn_r50_caffe_fpn_1x_nuim.py
+    Metadata:
+      Training Memory (GB): 7.0
+      Training Resources: 8x TITAN Xp
+    Results:
+      - Task: Object Detection
+        Dataset: nuImages
+        Metrics:
+          Box AP: 47.7
+      - Task: Instance Segmentation
+        Dataset: nuImages
+        Metrics:
+          Mask AP: 38.2
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_1x_nuim/
+
+  - Name: mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim
+    In Collection: Mask R-CNN
+    Config: configs/nuimages/mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim.py
+    Metadata:
+      Training Memory (GB): 7.0
+      Training Resources: 8x TITAN Xp
+    Results:
+      - Task: Object Detection
+        Dataset: nuImages
+        Metrics:
+          Box AP: 49.9
+      - Task: Instance Segmentation
+        Dataset: nuImages
+        Metrics:
+          Mask AP: 40.8
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim/mask_rcnn_r50_caffe_fpn_coco-3x_1x_nuim_20201008_195305-661a992e.pth
+
+  - Name: mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim
+    In Collection: Mask R-CNN
+    Config: configs/nuimages/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim.py
+    Metadata:
+      Training Memory (GB): 7.0
+      Training Resources: 8x TITAN Xp
+    Results:
+      - Task: Object Detection
+        Dataset: nuImages
+        Metrics:
+          Box AP: 50.6
+      - Task: Instance Segmentation
+        Dataset: nuImages
+        Metrics:
+          Mask AP: 41.3
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim/mask_rcnn_r50_caffe_fpn_coco-3x_20e_nuim_20201009_125002-5529442c.pth
+
+  - Name: mask_rcnn_r101_fpn_1x_nuim
+    In Collection: Mask R-CNN
+    Config: configs/nuimages/mask_rcnn_r101_fpn_1x_nuim.py
+    Metadata:
+      Training Memory (GB): 10.9
+      Training Resources: 8x TITAN Xp
+    Results:
+      - Task: Object Detection
+        Dataset: nuImages
+        Metrics:
+          Box AP: 48.9
+      - Task: Instance Segmentation
+        Dataset: nuImages
+        Metrics:
+          Mask AP: 39.1
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_r101_fpn_1x_nuim/mask_rcnn_r101_fpn_1x_nuim_20201024_134803-65c7623a.pth
+
+  - Name: mask_rcnn_x101_32x4d_fpn_1x_nuim
+    In Collection: Mask R-CNN
+    Config: configs/nuimages/mask_rcnn_x101_32x4d_fpn_1x_nuim.py
+    Metadata:
+      Training Memory (GB): 13.3
+      Training Resources: 8x TITAN Xp
+    Results:
+      - Task: Object Detection
+        Dataset: nuImages
+        Metrics:
+          Box AP: 50.4
+      - Task: Instance Segmentation
+        Dataset: nuImages
+        Metrics:
+          Mask AP: 40.5
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/mask_rcnn_x101_32x4d_fpn_1x_nuim/mask_rcnn_x101_32x4d_fpn_1x_nuim_20201024_135741-b699ab37.pth
+
+  - Name: cascade_mask_rcnn_r50_fpn_1x_nuim
+    In Collection: Mask R-CNN
+    Config: configs/nuimages/cascade_mask_rcnn_r50_fpn_1x_nuim.py
+    Metadata:
+      Training Memory (GB): 8.9
+      Training Resources: 8x TITAN Xp
+    Results:
+      - Task: Object Detection
+        Dataset: nuImages
+        Metrics:
+          Box AP: 50.8
+      - Task: Instance Segmentation
+        Dataset: nuImages
+        Metrics:
+          Mask AP: 40.4
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r50_fpn_1x_nuim/cascade_mask_rcnn_r50_fpn_1x_nuim_20201008_195342-1147c036.pth
+
+  - Name: cascade_mask_rcnn_r50_fpn_coco-20e_1x_nuim
+    In Collection: Mask R-CNN
+    Config: configs/nuimages/cascade_mask_rcnn_r50_fpn_coco-20e_1x_nuim.py
+    Metadata:
+      Training Memory (GB): 8.9
+      Training Resources: 8x TITAN Xp
+    Results:
+      - Task: Object Detection
+        Dataset: nuImages
+        Metrics:
+          Box AP: 52.8
+      - Task: Instance Segmentation
+        Dataset: nuImages
+        Metrics:
+          Mask AP: 42.2
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r50_fpn_coco-20e_1x_nuim/cascade_mask_rcnn_r50_fpn_coco-20e_1x_nuim_20201009_124158-ad0540e3.pth
+
+  - Name: cascade_mask_rcnn_r50_fpn_coco-20e_20e_nuim
+    In Collection: Mask R-CNN
+    Config: configs/nuimages/cascade_mask_rcnn_r50_fpn_coco-20e_20e_nuim.py
+    Metadata:
+      Training Memory (GB): 8.9
+      Training Resources: 8x TITAN Xp
+    Results:
+      - Task: Object Detection
+        Dataset: nuImages
+        Metrics:
+          Box AP: 52.8
+      - Task: Instance Segmentation
+        Dataset: nuImages
+        Metrics:
+          Mask AP: 42.2
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r50_fpn_coco-20e_20e_nuim/cascade_mask_rcnn_r50_fpn_coco-20e_20e_nuim_20201009_124951-40963960.pth
+
+  - Name: cascade_mask_rcnn_r101_fpn_1x_nuim
+    In Collection: Mask R-CNN
+    Config: configs/nuimages/cascade_mask_rcnn_r101_fpn_1x_nuim.py
+    Metadata:
+      Training Memory (GB): 12.5
+      Training Resources: 8x TITAN Xp
+    Results:
+      - Task: Object Detection
+        Dataset: nuImages
+        Metrics:
+          Box AP: 51.5
+      - Task: Instance Segmentation
+        Dataset: nuImages
+        Metrics:
+          Mask AP: 40.7
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_r101_fpn_1x_nuim/cascade_mask_rcnn_r101_fpn_1x_nuim_20201024_134804-45215b1e.pth
+
+  - Name: cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim
+    In Collection: Mask R-CNN
+    Config: configs/nuimages/cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim.py
+    Metadata:
+      Training Memory (GB): 14.9
+      Training Resources: 8x TITAN Xp
+    Results:
+      - Task: Object Detection
+        Dataset: nuImages
+        Metrics:
+          Box AP: 52.8
+      - Task: Instance Segmentation
+        Dataset: nuImages
+        Metrics:
+          Mask AP: 41.6
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim/cascade_mask_rcnn_x101_32x4d_fpn_1x_nuim_20201024_135753-e0e49778.pth
+
+  - Name: htc_r50_fpn_coco-20e_1x_nuim
+    In Collection: Mask R-CNN
+    Config: configs/nuimages/htc_r50_fpn_coco-20e_1x_nuim.py
+    Metadata:
+      Training Memory (GB): 11.6
+      Training Resources: 8x V100 GPUs
+    Results:
+      - Task: Object Detection
+        Dataset: nuImages
+        Metrics:
+          Box AP: 53.8
+      - Task: Instance Segmentation
+        Dataset: nuImages
+        Metrics:
+          Mask AP: 43.8
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/htc_r50_fpn_coco-20e_1x_nuim/htc_r50_fpn_coco-20e_1x_nuim_20201010_070203-0b53a65e.pth
+
+  - Name: htc_r50_fpn_coco-20e_20e_nuim
+    In Collection: Mask R-CNN
+    Config: configs/nuimages/htc_r50_fpn_coco-20e_20e_nuim.py
+    Metadata:
+      Training Memory (GB): 11.6
+      Training Resources: 8x V100 GPUs
+    Results:
+      - Task: Object Detection
+        Dataset: nuImages
+        Metrics:
+          Box AP: 54.8
+      - Task: Instance Segmentation
+        Dataset: nuImages
+        Metrics:
+          Mask AP: 44.4
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/htc_r50_fpn_coco-20e_20e_nuim/htc_r50_fpn_coco-20e_20e_nuim_20201008_211415-d6c60a2c.pth
+
+  - Name: htc_x101_64x4d_fpn_dconv_c3-c5_coco-20e_16x1_20e_nuim
+    In Collection: Mask R-CNN
+    Config: configs/nuimages/htc_x101_64x4d_fpn_dconv_c3-c5_coco-20e_16x1_20e_nuim.py
+    Metadata:
+      Training Memory (GB): 13.3
+      Training Resources: 8x V100 GPUs
+    Results:
+      - Task: Object Detection
+        Dataset: nuImages
+        Metrics:
+          Box AP: 57.3
+      - Task: Instance Segmentation
+        Dataset: nuImages
+        Metrics:
+          Mask AP: 46.4
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/nuimages_semseg/htc_x101_64x4d_fpn_dconv_c3-c5_coco-20e_16x1_20e_nuim/htc_x101_64x4d_fpn_dconv_c3-c5_coco-20e_16x1_20e_nuim_20201008_211222-0b16ac4b.pth

configs/parta2/metafile.yml

+Collections:
+  - Name: Part-A^2
+    Metadata:
+      Training Data: KITTI
+      Training Techniques:
+        - AdamW
+      Training Resources: 8x V100 GPUs
+      Architecture:
+        - Sparse U-Net
+    Paper: https://arxiv.org/abs/1907.03670
+    README: configs/parta2/README.md
+
+Models:
+  - Name: hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class
+    In Collection: Part-A^2
+    Config: configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class.py
+    Metadata:
+      Training Memory (GB): 4.1
+    Results:
+      - Task: 3D Object Detection
+        Dataset: KITTI
+        Metrics:
+          mAP: 67.9
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-3class_20200620_230724-a2672098.pth
+
+  - Name: hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-car
+    In Collection: Part-A^2
+    Config: configs/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-car.py
+    Metadata:
+      Training Memory (GB): 4.0
+    Results:
+      - Task: 3D Object Detection
+        Dataset: KITTI
+        Metrics:
+          mAP: 79.16
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/parta2/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-car/hv_PartA2_secfpn_2x8_cyclic_80e_kitti-3d-car_20200620_230755-f2a38b9a.pth

configs/pointpillars/metafile.yml

+Collections:
+  - Name: PointPillars
+    Metadata:
+      Training Techniques:
+        - AdamW
+      Architecture:
+        - Feature Pyramid Network
+    Paper: https://arxiv.org/abs/1812.05784
+    README: configs/pointpillars/README.md
+
+Models:
+  - Name: hv_pointpillars_secfpn_6x8_160e_kitti-3d-car
+    In Collection: PointPillars
+    Config: configs/pointpillars/hv_pointpillars_secfpn_6x8_160e_kitti-3d-car.py
+    Metadata:
+      Training Data: KITTI
+      Training Memory (GB): 5.4
+      Training Resources: 8x V100 GPUs
+    Results:
+      - Task: 3D Object Detection
+        Dataset: KITTI
+        Metrics:
+          AP: 77.1
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/pointpillars/hv_pointpillars_secfpn_6x8_160e_kitti-3d-car/hv_pointpillars_secfpn_6x8_160e_kitti-3d-car_20200620_230614-77663cd6.pth
+
+  - Name: hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class
+    In Collection: PointPillars
+    Config: configs/pointpillars/hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class.py
+    Metadata:
+      Training Data: KITTI
+      Training Memory (GB): 5.5
+      Training Resources: 8x V100 GPUs
+    Results:
+      - Task: 3D Object Detection
+        Dataset: KITTI
+        Metrics:
+          AP: 59.5
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/pointpillars/hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class/hv_pointpillars_secfpn_6x8_160e_kitti-3d-3class_20200620_230421-aa0f3adb.pth
+
+  - Name: hv_pointpillars_secfpn_sbn-all_4x8_2x_nus-3d
+    In Collection: PointPillars
+    Config: configs/pointpillars/hv_pointpillars_secfpn_sbn-all_4x8_2x_nus-3d.py
+    Metadata:
+      Training Data: nuScenes
+      Training Memory (GB): 16.4
+      Training Resources: 8x V100 GPUs
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 35.17
+          NDS: 49.7
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/pointpillars/hv_pointpillars_secfpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_secfpn_sbn-all_4x8_2x_nus-3d_20200620_230725-0817d270.pth
+
+  - Name: hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d
+    In Collection: PointPillars
+    Config: configs/pointpillars/hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d.py
+    Metadata:
+      Training Data: nuScenes
+      Training Memory (GB): 16.4
+      Training Resources: 8x V100 GPUs
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 40.0
+          NDS: 53.3
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/pointpillars/hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_fpn_sbn-all_4x8_2x_nus-3d_20200620_230405-2fa62f3d.pth
+
+  - Name: hv_pointpillars_secfpn_sbn-all_4x8_2x_lyft-3d
+    In Collection: PointPillars
+    Config: configs/pointpillars/hv_pointpillars_secfpn_sbn-all_4x8_2x_lyft-3d.py
+    Metadata:
+      Training Data: Lyft
+    Results:
+      - Task: 3D Object Detection
+        Dataset: Lyft
+        Metrics:
+          Private Score: 13.4
+          Public Score: 13.4
+
+  - Name: hv_pointpillars_fpn_sbn-all_4x8_2x_lyft-3d
+    In Collection: PointPillars
+    Config: configs/pointpillars/hv_pointpillars_fpn_sbn-all_4x8_2x_lyft-3d.py
+    Metadata:
+      Training Data: Lyft
+    Results:
+      - Task: 3D Object Detection
+        Dataset: Lyft
+        Metrics:
+          Private Score: 14.0
+          Public Score: 14.2
+
+  - Name: hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-car
+    In Collection: PointPillars
+    Config: configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-car.py
+    Metadata:
+      Training Data: Waymo
+      Training Memory (GB): 7.76
+      Training Resources: 8x GeForce GTX 1080 Ti
+    Results:
+      - Task: 3D Object Detection
+        Dataset: Waymo
+        Metrics:
+          mAP@L1: 70.2
+          mAPH@L1: 69.6
+          mAP@L2: 62.6
+          mAPH@L2: 62.1
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-car/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-car_20200901_204315-302fc3e7.pth
+
+  - Name: hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class
+    In Collection: PointPillars
+    Config: configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py
+    Metadata:
+      Training Data: Waymo
+      Training Memory (GB): 8.12
+      Training Resources: 8x GeForce GTX 1080 Ti
+    Results:
+      - Task: 3D Object Detection
+        Dataset: Waymo
+        Metrics:
+          mAP@L1: 64.7
+          mAPH@L1: 57.6
+          mAP@L2: 58.4
+          mAPH@L2: 52.1
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class/hv_pointpillars_secfpn_sbn_2x16_2x_waymoD5-3d-3class_20200831_204144-d1a706b1.pth
+
+  - Name: hv_pointpillars_secfpn_sbn_2x16_2x_waymo-3d-car
+    In Collection: PointPillars
+    Config: configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymo-3d-car.py
+    Metadata:
+      Training Data: Waymo
+      Training Memory (GB): 7.76
+      Training Resources: 8x GeForce GTX 1080 Ti
+    Results:
+      - Task: 3D Object Detection
+        Dataset: Waymo
+        Metrics:
+          mAP@L1: 72.1
+          mAPH@L1: 71.5
+          mAP@L2: 63.6
+          mAPH@L2: 63.1
+
+  - Name: hv_pointpillars_secfpn_sbn_2x16_2x_waymo-3d-3class
+    In Collection: PointPillars
+    Config: configs/pointpillars/hv_pointpillars_secfpn_sbn_2x16_2x_waymo-3d-3class.py
+    Metadata:
+      Training Data: Waymo
+      Training Memory (GB): 8.12
+      Training Resources: 8x GeForce GTX 1080 Ti
+    Results:
+      - Task: 3D Object Detection
+        Dataset: Waymo
+        Metrics:
+          mAP@L1: 68.8
+          mAPH@L1: 63.3
+          mAP@L2: 62.6
+          mAPH@L2: 57.6

configs/regnet/metafile.yml

+Collections:
+  - Name: RegNetX
+    Metadata:
+      Training Techniques:
+        - AdamW
+      Training Resources: 8x V100 GPUs
+      Architecture:
+        - Faster R-CNN
+        - Hard Voxelization
+    Paper: https://arxiv.org/abs/2003.13678
+    README: configs/regnet/README.md
+
+Models:
+  - Name: hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d
+    In Collection: RegNetX
+    Config: configs/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d.py
+    Metadata:
+      Training Data: nuScenes
+      Training Memory (GB): 16.4
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 41.2
+          NDS: 55.2
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_nus-3d_20200620_230334-53044f32.pth
+
+  - Name: hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d
+    In Collection: RegNetX
+    Config: configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d.py
+    Metadata:
+      Training Data: nuScenes
+      Training Memory (GB): 17.3
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 44.8
+          NDS: 56.4
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_nus-3d_20200620_230239-c694dce7.pth
+
+  - Name: hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d
+    In Collection: RegNetX
+    Config: configs/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d.py
+    Metadata:
+      Training Data: nuScenes
+      Training Memory (GB): 24.0
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 48.2
+          NDS: 59.3
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/regnet/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d/hv_pointpillars_regnet-1.6gf_fpn_sbn-all_4x8_2x_nus-3d_20200629_050311-dcd4e090.pth
+
+  - Name: hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_lyft-3d
+    In Collection: RegNetX
+    Config: configs/regnet/hv_pointpillars_regnet-400mf_secfpn_sbn-all_4x8_2x_lyft-3d.py
+    Metadata:
+      Training Data: Lyft
+    Results:
+      - Task: 3D Object Detection
+        Dataset: Lyft
+
+  - Name: hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_lyft-3d
+    In Collection: RegNetX
+    Config: configs/regnet/hv_pointpillars_regnet-400mf_fpn_sbn-all_4x8_2x_lyft-3d.py
+    Metadata:
+      Training Data: Lyft
+    Results:
+      - Task: 3D Object Detection
+        Dataset: Lyft
+        Metrics:
+          Private Score: 15.5
+          Public Score: 15.6

configs/second/metafile.yml

+Collections:
+  - Name: SECOND
+    Metadata:
+      Training Techniques:
+        - AdamW
+      Architecture:
+        - Hard Voxelization
+    Paper: https://www.mdpi.com/1424-8220/18/10/3337
+    README: configs/second/README.md
+
+Models:
+  - Name: hv_second_secfpn_6x8_80e_kitti-3d-car
+    In Collection: SECOND
+    Config: configs/second/hv_second_secfpn_6x8_80e_kitti-3d-car.py
+    Metadata:
+      Training Data: KITTI
+      Training Memory (GB): 5.4
+      Training Resources: 8x V100 GPUs
+    Results:
+      - Task: 3D Object Detection
+        Dataset: KITTI
+        Metrics:
+          mAP: 79.07
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/second/hv_second_secfpn_6x8_80e_kitti-3d-car/hv_second_secfpn_6x8_80e_kitti-3d-car_20200620_230238-393f000c.pth
+
+  - Name: hv_second_secfpn_6x8_80e_kitti-3d-3class
+    In Collection: SECOND
+    Config: configs/second/hv_second_secfpn_6x8_80e_kitti-3d-3class.py
+    Metadata:
+      Training Data: KITTI
+      Training Memory (GB): 5.4
+      Training Resources: 8x V100 GPUs
+    Results:
+      - Task: 3D Object Detection
+        Dataset: KITTI
+        Metrics:
+          mAP: 64.41
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/second/hv_second_secfpn_6x8_80e_kitti-3d-3class/hv_second_secfpn_6x8_80e_kitti-3d-3class_20200620_230238-9208083a.pth
+
+  - Name: hv_second_secfpn_sbn_2x16_2x_waymoD5-3d-3class
+    In Collection: SECOND
+    Config: configs/second/hv_second_secfpn_sbn_2x16_2x_waymoD5-3d-3class.py
+    Metadata:
+      Training Data: Waymo
+      Training Memory (GB): 8.12
+      Training Resources: 8x GeForce GTX 1080 Ti
+    Results:
+      - Task: 3D Object Detection
+        Dataset: Waymo
+        Metrics:
+          mAP@L1: 65.3
+          mAPH@L1: 61.7
+          mAP@L2: 58.9
+          mAPH@L2: 55.7

configs/ssn/metafile.yml

+Collections:
+  - Name: SSN
+    Metadata:
+      Training Techniques:
+        - AdamW
+      Training Resources: 8x GeForce GTX 1080 Ti
+      Architecture:
+        - Hard Voxelization
+    Paper: https://arxiv.org/abs/2004.02774
+    README: configs/ssn/README.md
+
+Models:
+  - Name: hv_ssn_secfpn_sbn-all_2x16_2x_nus-3d
+    In Collection: SSN
+    Config: configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_nus-3d.py
+    Metadata:
+      Training Data: nuScenes
+      Training Memory (GB): 9.62
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 41.56
+          NDS: 54.83
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_nus-3d/hv_ssn_secfpn_sbn-all_2x16_2x_nus-3d_20201023_193737-5fda3f00.pth
+
+  - Name: hv_ssn_regnet-400mf_secfpn_sbn-all_2x16_2x_nus-3d
+    In Collection: SSN
+    Config: configs/ssn/hv_ssn_regnet-400mf_secfpn_sbn-all_2x16_2x_nus-3d.py
+    Metadata:
+      Training Data: nuScenes
+      Training Memory (GB): 10.26
+    Results:
+      - Task: 3D Object Detection
+        Dataset: nuScenes
+        Metrics:
+          mAP: 46.95
+          NDS: 58.24
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/ssn/hv_ssn_regnet-400mf_secfpn_sbn-all_2x16_2x_nus-3d/hv_ssn_regnet-400mf_secfpn_sbn-all_2x16_2x_nus-3d_20201024_232447-7af3d8c8.pth
+
+  - Name: hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d
+    In Collection: SSN
+    Config: configs/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d.py
+    Metadata:
+      Training Data: Lyft
+      Training Memory (GB): 8.30
+    Results:
+      - Task: 3D Object Detection
+        Dataset: Lyft
+        Metrics:
+          Private Score: 17.4
+          Public Score: 17.5
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/ssn/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d/hv_ssn_secfpn_sbn-all_2x16_2x_lyft-3d_20201016_220844-3058d9fc.pth
+
+  - Name: hv_ssn_regnet-400mf_secfpn_sbn-all_1x16_2x_lyft-3d
+    In Collection: SSN
+    Config: configs/ssn/hv_ssn_regnet-400mf_secfpn_sbn-all_1x16_2x_lyft-3d.py
+    Metadata:
+      Training Data: Lyft
+      Training Memory (GB): 9.98
+    Results:
+      - Task: 3D Object Detection
+        Dataset: Lyft
+        Metrics:
+          Private Score: 18.1
+          Public Score: 18.3
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/ssn/hv_ssn_regnet-400mf_secfpn_sbn-all_2x16_2x_lyft-3d/hv_ssn_regnet-400mf_secfpn_sbn-all_2x16_2x_lyft-3d_20201025_213155-4532096c.pth

configs/votenet/metafile.yml

+Collections:
+  - Name: VoteNet
+    Metadata:
+      Training Techniques:
+        - AdamW
+      Training Resources: 8x V100 GPUs
+      Architecture:
+        - PointNet++
+    Paper: https://arxiv.org/abs/1904.09664
+    README: configs/votenet/README.md
+
+Models:
+  - Name: votenet_16x8_sunrgbd-3d-10class.py
+    In Collection: VoteNet
+    Config: configs/votenet/votenet_16x8_sunrgbd-3d-10class.py
+    Metadata:
+      Training Data: SUNRGBD
+      Training Memory (GB): 8.1
+    Results:
+      - Task: 3D Object Detection
+        Dataset: SUNRGBD
+        Metrics:
+          AP@0.25: 59.07
+          AP@0.5: 35.77
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/votenet/votenet_16x8_sunrgbd-3d-10class/votenet_16x8_sunrgbd-3d-10class_20200620_230238-4483c0c0.pth
+
+  - Name: votenet_8x8_scannet-3d-18class.py
+    In Collection: VoteNet
+    Config: configs/votenet/votenet_8x8_scannet-3d-18class.py
+    Metadata:
+      Training Data: ScanNet
+      Training Memory (GB): 4.1
+    Results:
+      - Task: 3D Object Detection
+        Dataset: ScanNet
+        Metrics:
+          AP@0.25: 62.90
+          AP@0.5: 39.91
+    Weights: https://download.openmmlab.com/mmdetection3d/v0.1.0_models/votenet/votenet_8x8_scannet-3d-18class/votenet_8x8_scannet-3d-18class_20200620_230238-2cea9c3a.pth
+
+  - Name: votenet_iouloss_8x8_scannet-3d-18class
+    In Collection: VoteNet
+    Config: configs/votenet/votenet_iouloss_8x8_scannet-3d-18class.py
+    Metadata:
+      Training Data: ScanNet
+      Training Memory (GB): 4.1
+      Architecture:
+        - IoU Loss
+    Results:
+      - Task: 3D Object Detection
+        Dataset: ScanNet
+        Metrics:
+          AP@0.25: 63.81
+          AP@0.5: 44.21

model_zoo.yml

+Import:
+  - configs/3dssd/metafile.yml
+  - configs/centerpoint/metafile.yml
+  - configs/dynamic_voxelization/metafile.yml
+  - configs/fp16/metafile.yml
+  - configs/free_anchor/metafile.yml
+  - configs/h3dnet/metafile.yml
+  - configs/imvotenet/metafile.yml
+  - configs/mvxnet/metafile.yml
+  - configs/nuimages/metafile.yml
+  - configs/parta2/metafile.yml
+  - configs/pointpillars/metafile.yml
+  - configs/regnet/metafile.yml
+  - configs/second/metafile.yml
+  - configs/ssn/metafile.yml
+  - configs/votenet/metafile.yml