Papers › DSGN: Deep Stereo Geometry Network for 3D Object Detection
DSGN: Deep Stereo Geometry Network for 3D Object Detection
Yilun Chen, Shu Liu, Xiaoyong Shen, Jiaya Jia
Most state-of-the-art 3D object detectors heavily rely on LiDAR sensors because there is a large performance gap between image-based and LiDAR-based methods. It is caused by the way to form representation for the prediction in 3D scenarios. Our method, called Deep Stereo Geometry Network (DSGN), significantly reduces this gap by detecting 3D objects on a differentiable volumetric representation -- 3D geometric volume, which effectively encodes 3D geometric structure for 3D regular space. With this representation, we learn depth information and semantic cues simultaneously. For the first time, we provide a simple and effective one-stage stereo-based 3D detection pipeline that jointly estimates the depth and detects 3D objects in an end-to-end learning manner. Our approach outperforms previous stereo-based 3D detectors (about 10 higher in terms of AP) and even achieves comparable performance with several LiDAR-based methods on the KITTI 3D object detection leaderboard. Our code is publicly available at https://github.com/chenyilun95/DSGN.
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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 From Stereo Images | KITTI Cars Moderate | DSGN | AP75 | 52.18 | #5 of 12 | Archive leaderboard | report |
| 3D Object Detection From Stereo Images | KITTI Cyclists Moderate | DSGN | AP50 | 18.17 | #4 of 5 | Archive leaderboard | report |
| 3D Object Detection From Stereo Images | KITTI Pedestrians Moderate | DSGN | AP50 | 15.55 | #6 of 6 | Archive leaderboard | report |
| Vehicle Pose Estimation | KITTI Cars Hard | DSGN (Stereo) | Average Orientation Similarity | 78.27 | #5 of 19 | 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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