Papers › IPOD: Intensive Point-based Object Detector for Point Cloud
IPOD: Intensive Point-based Object Detector for Point Cloud
Zetong Yang, Yanan sun, Shu Liu, Xiaoyong Shen, Jiaya Jia
We present a novel 3D object detection framework, named IPOD, based on raw point cloud. It seeds object proposal for each point, which is the basic element. This paradigm provides us with high recall and high fidelity of information, leading to a suitable way to process point cloud data. We design an end-to-end trainable architecture, where features of all points within a proposal are extracted from the backbone network and achieve a proposal feature for final bounding inference. These features with both context information and precise point cloud coordinates yield improved performance. We conduct experiments on KITTI dataset, evaluating our performance in terms of 3D object detection, Bird's Eye View (BEV) detection and 2D object detection. Our method accomplishes new state-of-the-art , showing great advantage on the hard set.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| 3D Object Detection | KITTI Cars Easy | IPOD | AP | 79.75% | #23 of 26 | Archive leaderboard | report |
| 3D Object Detection | KITTI Cars Hard | IPOD | AP | 66.33% | #20 of 25 | Archive leaderboard | report |
| 3D Object Detection | KITTI Cyclists Easy | IPOD | AP | 71.40% | #10 of 12 | Archive leaderboard | report |
| 3D Object Detection | KITTI Cyclists Hard | IPOD | AP | 48.34% | #10 of 12 | Archive leaderboard | report |
| 3D Object Detection | KITTI Cyclists Moderate | IPOD | AP | 53.46% | #11 of 13 | Archive leaderboard | report |
| 3D Object Detection | KITTI Pedestrians Easy | IPOD | AP | 56.92% | #1 of 9 | Archive leaderboard | report |
| 3D Object Detection | KITTI Pedestrians Hard | IPOD | AP | 42.39% | #2 of 9 | Archive leaderboard | report |
| 3D Object Detection | KITTI Pedestrians Moderate | IPOD | AP | 44.68% | #4 of 12 | 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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