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Dex-One2Many: Learning Dexterous Manipulation from a Single Human Demonstration

Paper recorded by Signals 4 on 2026-10-08 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-08 on arXiv · recorded by Signals 4 on 2026-10-09

Category: cs.CV · 计算机视觉 · first seen 2026-10-09

Abstract

While learning dexterous manipulation from a single human video offers a promising alternative to costly robot demonstrations, many recent methods predominantly imitate demonstrated motions. Such strict motion matching often limits generalization to initial object poses, goal poses, and grasps not shown in the video. Alternatively, discovering a policy via reinforcement learning (RL) allows for br

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#305 most recent of 756 cs.CV papers we have recorded · ↑ newer: Rubric-CEPR: Self-Evolving Image Editing via Reward-Verified Self-Dist · ↓ older: DreamTrue: Action-Faithful Robot World Model with Counterfactual Post-
Cite this page: Dex-One2Many: Learning Dexterous Manipulation from a Single Human Demonstration: the #305 most recent of 756 cs.CV papers we have recorded (as of 2026-10-08). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/dex-one2many-learning-dexterous-manipulation-from-a-single-human-demonstration.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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