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New system estimates 3D hand pose from room corners

By PulseAugur Editorial · [2 sources] ·

Researchers have developed REACH-Net, a novel 3D hand pose estimation system capable of accurately tracking hand shape and pose from fixed cameras in room corners. The system is designed to work with extremely low-resolution and occluded views by leveraging hand-body coordination and temporal progression. To train and evaluate REACH-Net, a new large-scale dataset called REACH was created, featuring 50 participants engaged in daily activities, with hand data captured via concealed chest cameras. AI

IMPACT Enables more robust 3D hand tracking in challenging, real-world environments for applications like human behavior analysis.

RANK_REASON The cluster contains a research paper detailing a new model and dataset for a specific computer vision task.

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Shu Nakamura, Ryo Kawahara, Genki Kinoshita, Ryosuke Hirai, Yasutomo Kawanishi, Shohei Nobuhara, Ko Nishino ·

    REACH: Hand Pose Estimation from Room Corners

    arXiv:2605.22231v1 Announce Type: new Abstract: We introduce a novel 3D hand pose estimator that can accurately recover the shape and pose of people's hands in a room from afar, typically from fixed cameras at room corners, in extremely low-resolution and frequently occluded view…

  2. arXiv cs.CV TIER_1 English(EN) · Ko Nishino ·

    REACH: Hand Pose Estimation from Room Corners

    We introduce a novel 3D hand pose estimator that can accurately recover the shape and pose of people's hands in a room from afar, typically from fixed cameras at room corners, in extremely low-resolution and frequently occluded views. Our key idea is to fully leverage hand-body c…

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