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arXiv · 2609.06955

Joint-Conditioned Stereo Surface Reasoning for Interaction Field Estimation

Yanlin Jin·Yifan Yang·Bowen Yang·Kai Zhu
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Abstract

Predicting hand--object interaction fields requires locating the nearest object-surface point for each hand joint, often from small and partially occluded image regions. We view this task as joint-conditioned surface-endpoint estimation: each joint has its own nearest endpoint, while endpoints from the same hand can draw on shared local surface evidence. This structure motivates Joint-Conditioned Stereo Surface Reasoning (JSSR). A temporal-stereo network jointly predicts 3D joints, a direct interaction field, and per-view endpoint evidence. Calibrated candidate search evaluates endpoint hypotheses using joint-specific image compatibility and cross-view correspondence. A hand-shared candidate support lets joints draw on common surface evidence, and a learned residual gate controls the geometric correction when observations are ambiguous. Our system built on this method ranked third on the SHOW3D Interaction Field Challenge leaderboard.

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Yanlin Jin, Yifan Yang, Bowen Yang, Kai Zhu. 2026-09-07. Joint-Conditioned Stereo Surface Reasoning for Interaction Field Estimation. https://arxiv.org/abs/2609.06955

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