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FingerViP: Learning Real-World Dexterous Manipulation with Fingertip Visual Perception
Current dexterous manipulation systems commonly rely on external or wrist-mounted cameras for visual feedback. However, such sensing setups are prone to occlusion and can limit performance on tasks requiring close-range, multi-view perception. In this work, we design a vision-enhanced fingertip modu
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