3DPSR: An innovative approach for pose and shape refinement in 3D human meshes from a single 2D image

Abstract

In the era of computer vision, 3D human models are gaining a lot of interest in the gaming industry, cloth parsing, avatar creations, and many more applications. In these fields, having a precise 3D human model with accurate shape and pose is crucial for realistic and high-quality results. We proposed an approach called 3DPSR that uses a single 2D image and reconstructs precise 3D human meshes with better alignment of pose and shape. 3DPSR is referred to as 3D Pose and Shape Refinements. 3DPSR contains two modules (mesh deformation using pose-fitting and shape-fitting), in which mesh deformation using shape-fitting acts as a refinement module. Compared to existing methods, the proposed method, 3DPSR, delivers more enhanced MPVE and PA-MPJPE results, as well as more accurate 3D models of humans. 3DPSR significantly outperforms state-of-the-art human mesh reconstruction methods on challenging and standard datasets such as SURREAL, Human3.6M, and 3DPW across different scenarios with complex poses, establishing a new benchmark.