Any6D: Model-free 6D Pose Estimation of Novel Objects
About
We introduce Any6D, a model-free framework for 6D object pose estimation that requires only a single RGB-D anchor image to estimate both the 6D pose and size of unknown objects in novel scenes. Unlike existing methods that rely on textured 3D models or multiple viewpoints, Any6D leverages a joint object alignment process to enhance 2D-3D alignment and metric scale estimation for improved pose accuracy. Our approach integrates a render-and-compare strategy to generate and refine pose hypotheses, enabling robust performance in scenarios with occlusions, non-overlapping views, diverse lighting conditions, and large cross-environment variations. We evaluate our method on five challenging datasets: REAL275, Toyota-Light, HO3D, YCBINEOAT, and LM-O, demonstrating its effectiveness in significantly outperforming state-of-the-art methods for novel object pose estimation. Project page: https://taeyeop.com/any6d
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| 6D Object Pose Estimation | Toyota-Light (TOYL) (test) | AR43.3 | 18 | |
| 6D Object Pose Estimation | REAL275 | ADD(-S)53.5 | 11 | |
| Object 6DoF Pose Estimation | HOI4D | Local RRE29.07 | 7 | |
| Relative Pose Estimation | Toyota-Light | ADD(-S)32.2 | 7 | |
| Object 6DoF Tracking | H2O | Local RRE38.54 | 7 | |
| 6D Object Pose Estimation | YCBInEOAT | AUC (ADD-S)89.3 | 4 | |
| 6D Object Pose Estimation | HO3D v2 (test) | ADD-S98.7 | 4 | |
| 6D Object Pose Estimation | Linemod Occlusion (LM-O) | AR28.6 | 3 |