W-HMR: Monocular Human Mesh Recovery in World Space with Weak-Supervised Calibration
This addresses the problem of misaligned 3D human reconstructions in real-world applications for computer vision researchers, though it appears incremental as it builds on existing methods with novel modules.
The paper tackles the problem of inaccurate 3D human motion recovery from monocular images due to reliance on camera coordinates and limited focal length labels, by introducing W-HMR, a weak-supervised calibration method that predicts focal lengths and corrects body orientation, resulting in improved accuracy and generalizability validated on various datasets.
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/.