手と物体のインタラクション検出の改善と評価
Improving and Evaluating Hand-Object Interaction Detection
手と物体のインタラクション検出を改善する新しいフレームワークHOI-DETRを提案し、複数のデータセットで最先端の性能を達成した。
著者: Ahmad Darkhalil, Dima Damen, David Fouhey
分類: cs.CV
原文アブストラクト
Understanding hands and the objects they interact with, both directly and through tools, is a key step for tasks ranging from action perception to 3D reconstruction and robotics. Our paper provides several contributions to the Hand-Object Interaction (HOI) understanding literature: (1) HOI-DETR, a new framework that introduces hand-object and object-object interactions to the Co-DETR architecture to produce a state-of-the-art method; (2) a comprehensive HOI evaluation suite of 4 diverse datasets, including a video benchmark derived from the HD-EPIC dataset and fresh annotations that improve the Hands23 benchmark and (3) a trained checkpoint that significantly improves the state of the art across Hands23, HOIST, FineBio, and HD-EPIC, including mAP gains of over 20 percentage points on Hands23 and FineBio. Our ablations confirm the contributions of each model component.