Abstract

Prior-free 6D object pose tracking seeks to recover the trajectory of an unseen object from a single RGB video without object-specific CAD models, posed reference images, or pose annotations. Geometric foundation models provide complementary object-centric and scene-centric cues, yet SAM3D CAD is indexed by an arbitrary object-local surface parameterization, whereas reconstructed evidence is expressed in a sequence-specific world frame with partial surface coverage. To exploit this complementarity, we formulate tracking as generation-reconstruction correspondence and introduce GRC-Pose, a correspondence-based framework that combines learned correspondence prediction with robust pose estimation. Concretely, GeoCorr-Matcher estimates weighted object-scene correspondences and per-match uncertainty for each pose candidate. FGH-Solver integrates these matches through multiple robust geometric estimators and sequence-level posterior inference, while a posterior-gated memory retains only inlier-supported observations through occlusion and viewpoint change. Extensive evaluation shows that with SAM3D CAD, GRC-Pose achieves state-of-the-art Average Recall and motion retention on HOT3D, improving the latter by 58% over prior art. On classical benchmarks including YCBInEOAT and LINEMOD, it remains highly competitive.

Keywords

Publication details

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Open access
Green open access

Cite this article

APA 7

Liu, S., Lin, W., Xiao, L., Tang, J., Yang, Y., Gao, Y., & Chen, X. (2026). GRC-Pose: Generation-Reconstruction Correspondence for Prior-Free 6D Object Pose Tracking. https://omanscience.com/en/articles/grc-pose-generation-reconstruction-correspondence-for-prior-free-6d-object-pose-tracking

MLA 9

Liu, Shiyang, et al. "GRC-Pose: Generation-Reconstruction Correspondence for Prior-Free 6D Object Pose Tracking." https://omanscience.com/en/articles/grc-pose-generation-reconstruction-correspondence-for-prior-free-6d-object-pose-tracking.

Chicago (author–date)

Liu, Shiyang, Weiquan Lin, Luping Xiao, Jiadong Tang, Yi Yang, Yu Gao, and Xingyu Chen. 2026. "GRC-Pose: Generation-Reconstruction Correspondence for Prior-Free 6D Object Pose Tracking." https://omanscience.com/en/articles/grc-pose-generation-reconstruction-correspondence-for-prior-free-6d-object-pose-tracking.

Harvard

Liu, S., Lin, W., Xiao, L., Tang, J., Yang, Y., Gao, Y. and Chen, X. (2026) 'GRC-Pose: Generation-Reconstruction Correspondence for Prior-Free 6D Object Pose Tracking', Available at: https://omanscience.com/en/articles/grc-pose-generation-reconstruction-correspondence-for-prior-free-6d-object-pose-tracking.

Vancouver

Liu S, Lin W, Xiao L, Tang J, Yang Y, Gao Y, et al. GRC-Pose: Generation-Reconstruction Correspondence for Prior-Free 6D Object Pose Tracking. https://omanscience.com/en/articles/grc-pose-generation-reconstruction-correspondence-for-prior-free-6d-object-pose-tracking

IEEE

S. Liu, W. Lin, L. Xiao, J. Tang, Y. Yang, Y. Gao, and X. Chen, "GRC-Pose: Generation-Reconstruction Correspondence for Prior-Free 6D Object Pose Tracking," https://omanscience.com/en/articles/grc-pose-generation-reconstruction-correspondence-for-prior-free-6d-object-pose-tracking.