Papers › PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection

PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection

31 Dec 2019CVPR 2020 6arXiv:1912.13192archive 2025-07-28

Shaoshuai Shi, Chaoxu Guo, Li Jiang, Zhe Wang, Jianping Shi, Xiaogang Wang, Hongsheng Li

We present a novel and high-performance 3D object detection framework, named PointVoxel-RCNN (PV-RCNN), for accurate 3D object detection from point clouds. Our proposed method deeply integrates both 3D voxel Convolutional Neural Network (CNN) and PointNet-based set abstraction to learn more discriminative point cloud features. It takes advantages of efficient learning and high-quality proposals of the 3D voxel CNN and the flexible receptive fields of the PointNet-based networks. Specifically, the proposed framework summarizes the 3D scene with a 3D voxel CNN into a small set of keypoints via a novel voxel set abstraction module to save follow-up computations and also to encode representative scene features. Given the high-quality 3D proposals generated by the voxel CNN, the RoI-grid pooling is proposed to abstract proposal-specific features from the keypoints to the RoI-grid points via keypoint set abstraction with multiple receptive fields. Compared with conventional pooling operations, the RoI-grid feature points encode much richer context information for accurately estimating object confidences and locations. Extensive experiments on both the KITTI dataset and the Waymo Open dataset show that our proposed PV-RCNN surpasses state-of-the-art 3D detection methods with remarkable margins by using only point clouds. Code is available at https://github.com/open-mmlab/OpenPCDet.

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open-mmlab/OpenPCDet officialmentioned in papermentioned on GitHubpytorchApache-2.0 report
KPeng9510/MASS mentioned on GitHubpytorchApache-2.0 report
KangchengLiu/RM3D mentioned on GitHubpytorch report
jhultman/PV-RCNN mentioned on GitHubpytorchMIT report
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box3d_to_bev_corners jhultman/PV-RCNN/vision3d/core/geometry.py community (archive-listed) ran MIT (permissive) · 174d1179819a5285 · report
clipped_percentile jhultman/PV-RCNN/vision3d/core/bev_drawer.py community (archive-listed) ran fingerprinted MIT (permissive) · 52b41e094461dcb7 · report
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encode jhultman/PV-RCNN/vision3d/core/box_encode.py community (archive-listed) ran MIT (permissive) · 744899d028ceaeb6 · report
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points_in_convex_polygon jhultman/PV-RCNN/vision3d/core/geometry.py community (archive-listed) ran MIT (permissive) · 808098fcbc06df78 · report
recursive_glob KPeng9510/MASS/label_processing_tools/gt_img.py community (archive-listed) ran fingerprinted Apache-2.0 (permissive) · 513d282e7c3d723b · report
torchify_anchor_attributes jhultman/PV-RCNN/vision3d/core/anchor_generator.py community (archive-listed) ran MIT (permissive) · bdb22c3ca2ff101f · report
cfg_from_yaml_file KPeng9510/MASS/pcdet/config.py community (archive-listed) unverified Apache-2.0 (permissive) · 696fe155f9990d38 · report
get_corner_loss_lidar KPeng9510/MASS/pcdet/utils/loss_utils.py community (archive-listed) unverified Apache-2.0 (permissive) · 1780d388cc532a6d · report
get_image_path sunshenggu/xc_eval_pcdet/pcdet/datasets/kitti/kitti_object_eval_python/kitti_common.py community (archive-listed) unverified Apache-2.0 (permissive) · c8b847449b3be5dc · report
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make_bev_map jhultman/PV-RCNN/vision3d/core/bev_drawer.py community (archive-listed) unverified MIT (permissive) · 7641b2131879260e · report
merge_new_config KPeng9510/MASS/pcdet/config.py community (archive-listed) unverified Apache-2.0 (permissive) · 392c0cf3a1b07b12 · report

Tasks

3D Object DetectionObjectObject DetectionRobust 3D Object Detectionobject-detection

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
3D Object Detection KITTI Cars Easy PV-RCNN AP 90.25% #8 of 26 Archive leaderboard report
3D Object Detection KITTI Cars Hard PV-RCNN AP 76.82% #8 of 25 Archive leaderboard report
3D Object Detection KITTI Cyclists Easy PV-RCNN AP 78.60% #6 of 12 Archive leaderboard report
3D Object Detection KITTI Cyclists Hard PV-RCNN AP 57.65% #3 of 12 Archive leaderboard report
3D Object Detection KITTI Cyclists Moderate PV-RCNN AP 63.71% #5 of 13 Archive leaderboard report
3D Object Detection waymo all_ns PV-RCNN APH/L2 71.52 #2 of 2 Archive leaderboard report
3D Object Detection waymo cyclist PV-RCNN APH/L2 71.16 #5 of 7 Archive leaderboard report
3D Object Detection waymo pedestrian PV-RCNN APH/L2 70.16 #6 of 7 Archive leaderboard report
3D Object Detection waymo vehicle PV-RCNN APH/L2 73.23 #4 of 8 Archive leaderboard report
Birds Eye View Object Detection KITTI Cars Easy PV-RCNN AP 94.98 #2 of 9 Archive leaderboard report
Birds Eye View Object Detection KITTI Cars Hard PV-RCNN AP 86.14 #3 of 8 Archive leaderboard report
Birds Eye View Object Detection KITTI Cars Moderate PV-RCNN AP 90.65% #2 of 9 Archive leaderboard report
Birds Eye View Object Detection KITTI Cyclists Easy PV-RCNN AP 82.49 #1 of 2 Archive leaderboard report
Birds Eye View Object Detection KITTI Cyclists Hard PV-RCNN AP 62.41 #1 of 2 Archive leaderboard report
Birds Eye View Object Detection KITTI Cyclists Moderate PV-RCNN AP 68.89% #1 of 6 Archive leaderboard report
Robust 3D Object Detection KITTI-C PV-RCNN mean Corruption Error (mCE) 90.04% #1 of 5 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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