Papers › MobilePose: Real-Time Pose Estimation for Unseen Objects with Weak Shape Supervision
MobilePose: Real-Time Pose Estimation for Unseen Objects with Weak Shape Supervision
Tingbo Hou, Adel Ahmadyan, Liangkai Zhang, Jianing Wei, Matthias Grundmann
In this paper, we address the problem of detecting unseen objects from RGB images and estimating their poses in 3D. We propose two mobile friendly networks: MobilePose-Base and MobilePose-Shape. The former is used when there is only pose supervision, and the latter is for the case when shape supervision is available, even a weak one. We revisit shape features used in previous methods, including segmentation and coordinate map. We explain when and why pixel-level shape supervision can improve pose estimation. Consequently, we add shape prediction as an intermediate layer in the MobilePose-Shape, and let the network learn pose from shape. Our models are trained on mixed real and synthetic data, with weak and noisy shape supervision. They are ultra lightweight that can run in real-time on modern mobile devices (e.g. 36 FPS on Galaxy S20). Comparing with previous single-shot solutions, our method has higher accuracy, while using a significantly smaller model (2~3% in model size or number of parameters).
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Monocular 3D Object Detection | Google Objectron | MobilePose | AP at 10' Elevation error | 0.6658 | #3 of 3 | Archive leaderboard | report |
| Monocular 3D Object Detection | Google Objectron | MobilePose | AP at 15' Azimuth error | 0.5088 | #3 of 3 | Archive leaderboard | report |
| Monocular 3D Object Detection | Google Objectron | MobilePose | Average Precision at 0.5 3D IoU | 0.4624 | #3 of 3 | Archive leaderboard | report |
| Monocular 3D Object Detection | Google Objectron | MobilePose | MPE | 0.1001 | #3 of 3 | 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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