Any6D: Model-free 6D Pose Estimation of Novel Objects
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
67e34bdb8aa257f5a3ebe346
Taeyeop Lee
claimed_verified
2025-03-26T20:45:09.497Z
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Taeyeop Lee
user
taeyeop
67e34bdb8aa257f5a3ebe347
Bowen Wen
67e34bdb8aa257f5a3ebe348
Minjun Kang
67e34bdb8aa257f5a3ebe349
Gyuree Kang
67e34bdb8aa257f5a3ebe34a
In So Kweon
67e34bdb8aa257f5a3ebe34b
Kuk-Jin Yoon
Any6D: Model-free 6D Pose Estimation of Novel Objects
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
Any6D estimates the 6D pose and size of unknown objects using a single RGB-D image through a model-free framework, enhancing 2D-3D alignment and scale estimation across challenging conditions.
6D object pose estimation RGB-D anchor image 2D-3D alignment metric scale estimation render-and-compare strategy pose hypotheses occlusions non-overlapping views diverse lighting conditions cross-environment variations REAL275 Toyota-Light HO3D YCBINEOAT LM-O