mlsanityData to 7 Oct 2026

Complementing Event Streams and RGB Frames for Hand Mesh Reconstruction

arXiv 2403.07346 ↗First posted 12 Mar 2024cs.CVcited by 14

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Abstract (arXiv)

Reliable hand mesh reconstruction (HMR) from commonly-used color and depth sensors is challenging especially under scenarios with varied illuminations and fast motions. Event camera is a highly promising alternative for its high dynamic range and dense temporal resolution properties, but it lacks key texture appearance for hand mesh reconstruction. In this paper, we propose EvRGBHand -- the first approach for 3D hand mesh reconstruction with an event camera and an RGB camera compensating for each other. By fusing two modalities of data across time, space, and information dimensions,EvRGBHand can tackle overexposure and motion blur issues in RGB-based HMR and foreground scarcity and background overflow issues in event-based HMR. We further propose EvRGBDegrader, which allows our model to generalize effectively in challenging scenes, even when trained solely on standard scenes, thus reducing data acquisition costs. Experiments on real-world data demonstrate that EvRGBHand can effectively solve the challenging issues when using either type of camera alone via retaining the merits of both, and shows the potential of generalization to outdoor scenes and another type of event camera.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 45 of its 72 references that are in the map. First posted on arXiv 12 Mar 2024.

Builds on

45 of 72 references.

References · 45

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33 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 4; 2025: 7; 2026: 3.

14 papers.

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