mlsanityData to 7 Oct 2026

POEM: Reconstructing Hand in a Point Embedded Multi-view Stereo

arXiv 2304.04038 ↗First posted 8 Apr 2023cs.CVcited by 9

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Abstract (arXiv)

Enable neural networks to capture 3D geometrical-aware features is essential in multi-view based vision tasks. Previous methods usually encode the 3D information of multi-view stereo into the 2D features. In contrast, we present a novel method, named POEM, that directly operates on the 3D POints Embedded in the Multi-view stereo for reconstructing hand mesh in it. Point is a natural form of 3D information and an ideal medium for fusing features across views, as it has different projections on different views. Our method is thus in light of a simple yet effective idea, that a complex 3D hand mesh can be represented by a set of 3D points that 1) are embedded in the multi-view stereo, 2) carry features from the multi-view images, and 3) encircle the hand. To leverage the power of points, we design two operations: point-based feature fusion and cross-set point attention mechanism. Evaluation on three challenging multi-view datasets shows that POEM outperforms the state-of-the-art in hand mesh reconstruction. Code and models are available for research at https://github.com/lixiny/POEM.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 53 of its 59 references that are in the map. First posted on arXiv 8 Apr 2023.

Builds on

53 of 59 references.

References · 53

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38 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 4; 2025: 2; 2026: 3.

9 papers.