PointPillars: Fast Encoders for Object Detection from Point Clouds

CVPR 2019 Alex H. LangSourabh VoraHolger CaesarLubing ZhouJiong YangOscar Beijbom

Object detection in point clouds is an important aspect of many robotics applications such as autonomous driving. In this paper we consider the problem of encoding a point cloud into a format appropriate for a downstream detection pipeline... (read more)

PDF Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Object Detection KITTI Cars Easy PointPillars AP 79.05 # 5
Birds Eye View Object Detection KITTI Cars Easy PointPillars AP 88.35 # 6
Birds Eye View Object Detection KITTI Cars Hard PointPillars AP 79.83 # 3
Object Detection KITTI Cars Moderate PointPillars AP 74.99 # 3
3D Object Detection KITTI Cars Moderate PointPillars AP 74.99% # 9
Birds Eye View Object Detection KITTI Cars Moderate PointPillars AP 86.10% # 4
3D Object Detection KITTI Cyclists Easy PointPillars AP 75.78% # 5
3D Object Detection KITTI Cyclists Hard PointPillars AP 52.92% # 6
Birds Eye View Object Detection KITTI Cyclists Moderate PointPillars AP 62.25% # 3
3D Object Detection KITTI Cyclists Moderate PointPillars AP 59.07% # 6
3D Object Detection KITTI Pedestrians Moderate PointPillars AP 41.92% # 8
Birds Eye View Object Detection KITTI Pedestrians Moderate PointPillars AP 50.23% # 3

Methods used in the Paper


METHOD TYPE
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