関節条件付きステレオ表面推論によるインタラクションフィールド推定
Joint-Conditioned Stereo Surface Reasoning for Interaction Field Estimation
手と物体のインタラクションフィールド推定を、各関節の最近傍表面点を推定する問題として捉え、時間ステレオネットワークと関節条件付き候補探索を用いた手法JSSRを提案した。
著者: Yanlin Jin, Yifan Yang, Bowen Yang, Kai Zhu
分類: cs.CV, cs.RO
原文アブストラクト
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.