W-HMR: Monocular Human Mesh Recovery in World Space with Weak-Supervised Calibration
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2023
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866914942316183552 |
|---|---|
| author | Yao, Wei Zhang, Hongwen Sun, Yunlian Liu, Yebin Tang, Jinhui |
| author_facet | Yao, Wei Zhang, Hongwen Sun, Yunlian Liu, Yebin Tang, Jinhui |
| contents | Previous methods for 3D human motion recovery from monocular images often fall short due to reliance on camera coordinates, leading to inaccuracies in real-world applications. The limited availability and diversity of focal length labels further exacerbate misalignment issues in reconstructed 3D human bodies. To address these challenges, we introduce W-HMR, a weak-supervised calibration method that predicts "reasonable" focal lengths based on body distortion information, eliminating the need for precise focal length labels. Our approach enhances 2D supervision precision and recovery accuracy. Additionally, we present the OrientCorrect module, which corrects body orientation for plausible reconstructions in world space, avoiding the error accumulation associated with inaccurate camera rotation predictions. Our contributions include a novel weak-supervised camera calibration technique, an effective orientation correction module, and a decoupling strategy that significantly improves the generalizability and accuracy of human motion recovery in both camera and world coordinates. The robustness of W-HMR is validated through extensive experiments on various datasets, showcasing its superiority over existing methods. Codes and demos have been made available on the project page https://yw0208.github.io/w-hmr/. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_17460 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | W-HMR: Monocular Human Mesh Recovery in World Space with Weak-Supervised Calibration Yao, Wei Zhang, Hongwen Sun, Yunlian Liu, Yebin Tang, Jinhui Computer Vision and Pattern Recognition Previous methods for 3D human motion recovery from monocular images often fall short due to reliance on camera coordinates, leading to inaccuracies in real-world applications. The limited availability and diversity of focal length labels further exacerbate misalignment issues in reconstructed 3D human bodies. To address these challenges, we introduce W-HMR, a weak-supervised calibration method that predicts "reasonable" focal lengths based on body distortion information, eliminating the need for precise focal length labels. Our approach enhances 2D supervision precision and recovery accuracy. Additionally, we present the OrientCorrect module, which corrects body orientation for plausible reconstructions in world space, avoiding the error accumulation associated with inaccurate camera rotation predictions. Our contributions include a novel weak-supervised camera calibration technique, an effective orientation correction module, and a decoupling strategy that significantly improves the generalizability and accuracy of human motion recovery in both camera and world coordinates. The robustness of W-HMR is validated through extensive experiments on various datasets, showcasing its superiority over existing methods. Codes and demos have been made available on the project page https://yw0208.github.io/w-hmr/. |
| title | W-HMR: Monocular Human Mesh Recovery in World Space with Weak-Supervised Calibration |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2311.17460 |