Scaling up parametric human recovery - Cai, Zhongang (Nanyang Technological University, 2024)
This thesis addresses the fundamental tasks of parametric human recovery (i.e. human pose and shape estimation with parametric human models) from monocular images or videos, a field with wide-ranging applications. The key goal is to develop the first foundation model for human parametric pose and shape recovery. A critical challenge in achieving this is the prohibitive cost of acquiring large-scale, diverse datasets, which limits the accuracy and generalizability of state-of-the-art methods. To overcome this, the thesis presents a cohesive series of innovative studies aimed at resolving data scarcity. These studies culminate in a comprehensive investigation that utilizes an extensive range of data to explore scaling laws in parametric human recovery. Collectively, these efforts mark a significant advancement in the field through scaling up toward an unprecedentedly robust, high-performance parametric human recovery in the wild.