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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.16137 |
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| _version_ | 1866914846802444288 |
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| author | Yang, Jian Li, Jiakun Li, Guoming Shen, Zhen Wu, Huai-Yu Fan, Zhaoxin Huang, Heng |
| author_facet | Yang, Jian Li, Jiakun Li, Guoming Shen, Zhen Wu, Huai-Yu Fan, Zhaoxin Huang, Heng |
| contents | Multi-view hand mesh reconstruction is a critical task for applications in virtual reality and human-computer interaction, but it remains a formidable challenge. Although existing multi-view hand reconstruction methods achieve remarkable accuracy, they typically come with an intensive computational burden that hinders real-time inference. To this end, we propose MLPHand, a novel method designed for real-time multi-view single hand reconstruction. MLP Hand consists of two primary modules: (1) a lightweight MLP-based Skeleton2Mesh model that efficiently recovers hand meshes from hand skeletons, and (2) a multi-view geometry feature fusion prediction module that enhances the Skeleton2Mesh model with detailed geometric information from multiple views. Experiments on three widely used datasets demonstrate that MLPHand can reduce computational complexity by 90% while achieving comparable reconstruction accuracy to existing state-of-the-art baselines. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_16137 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | MLPHand: Real Time Multi-View 3D Hand Mesh Reconstruction via MLP Modeling Yang, Jian Li, Jiakun Li, Guoming Shen, Zhen Wu, Huai-Yu Fan, Zhaoxin Huang, Heng Computer Vision and Pattern Recognition Multi-view hand mesh reconstruction is a critical task for applications in virtual reality and human-computer interaction, but it remains a formidable challenge. Although existing multi-view hand reconstruction methods achieve remarkable accuracy, they typically come with an intensive computational burden that hinders real-time inference. To this end, we propose MLPHand, a novel method designed for real-time multi-view single hand reconstruction. MLP Hand consists of two primary modules: (1) a lightweight MLP-based Skeleton2Mesh model that efficiently recovers hand meshes from hand skeletons, and (2) a multi-view geometry feature fusion prediction module that enhances the Skeleton2Mesh model with detailed geometric information from multiple views. Experiments on three widely used datasets demonstrate that MLPHand can reduce computational complexity by 90% while achieving comparable reconstruction accuracy to existing state-of-the-art baselines. |
| title | MLPHand: Real Time Multi-View 3D Hand Mesh Reconstruction via MLP Modeling |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2406.16137 |