Papers › ES6D: A Computation Efficient and Symmetry-Aware 6D Pose Regression Framework
ES6D: A Computation Efficient and Symmetry-Aware 6D Pose Regression Framework
Ningkai Mo, Wanshui Gan, Naoto Yokoya, Shifeng Chen
In this paper, a computation efficient regression framework is presented for estimating the 6D pose of rigid objects from a single RGB-D image, which is applicable to handling symmetric objects. This framework is designed in a simple architecture that efficiently extracts point-wise features from RGB-D data using a fully convolutional network, called XYZNet, and directly regresses the 6D pose without any post refinement. In the case of symmetric object, one object has multiple ground-truth poses, and this one-to-many relationship may lead to estimation ambiguity. In order to solve this ambiguity problem, we design a symmetry-invariant pose distance metric, called average (maximum) grouped primitives distance or A(M)GPD. The proposed A(M)GPD loss can make the regression network converge to the correct state, i.e., all minima in the A(M)GPD loss surface are mapped to the correct poses. Extensive experiments on YCB-Video and T-LESS datasets demonstrate the proposed framework's substantially superior performance in top accuracy and low computational cost.
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Code
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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 | DTTD-Mobile | ES6D | ADD AUC | 13.25 | #5 of 5 | Archive leaderboard | report |
| 3D Object Detection | DTTD-Mobile | ES6D | ADD-S AUC | 37.38 | #5 of 5 | Archive leaderboard | report |
| 6D Pose Estimation | DTTD-Mobile | ES6D | ADD AUC | 13.25 | #4 of 8 | Archive leaderboard | report |
| 6D Pose Estimation | DTTD-Mobile | ES6D | ADD-S AUC | 37.38 | #4 of 8 | 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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