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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

Taeyeop Lee, Bowen Wen, Minjun Kang, Gyuree Kang, In So Kweon, Kuk-Jin Yoon• 2025

Related benchmarks

TaskDatasetResultRank
6D Object Pose EstimationToyota-Light (TOYL) (test)
AR43.3
18
6D Object Pose EstimationREAL275
ADD(-S)53.5
11
Object 6DoF Pose EstimationHOI4D
Local RRE29.07
7
Relative Pose EstimationToyota-Light
ADD(-S)32.2
7
Object 6DoF TrackingH2O
Local RRE38.54
7
6D Object Pose EstimationYCBInEOAT
AUC (ADD-S)89.3
4
6D Object Pose EstimationHO3D v2 (test)
ADD-S98.7
4
6D Object Pose EstimationLinemod Occlusion (LM-O)
AR28.6
3
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