Link to the Past: Temporal Propagation for Fast 3D Human Reconstruction from Monocular Video
This addresses the challenge of real-time 3D human reconstruction for applications like virtual reality or animation, though it is incremental as it builds on existing pixel-aligned networks.
The paper tackles fast 3D clothed human reconstruction from monocular video by introducing TemPoFast3D, which leverages temporal coherency to reduce redundant computation, achieving up to 12 FPS while matching or exceeding state-of-the-art methods in quality.
Fast 3D clothed human reconstruction from monocular video remains a significant challenge in computer vision, particularly in balancing computational efficiency with reconstruction quality. Current approaches are either focused on static image reconstruction but too computationally intensive, or achieve high quality through per-video optimization that requires minutes to hours of processing, making them unsuitable for real-time applications. To this end, we present TemPoFast3D, a novel method that leverages temporal coherency of human appearance to reduce redundant computation while maintaining reconstruction quality. Our approach is a "plug-and play" solution that uniquely transforms pixel-aligned reconstruction networks to handle continuous video streams by maintaining and refining a canonical appearance representation through efficient coordinate mapping. Extensive experiments demonstrate that TemPoFast3D matches or exceeds state-of-the-art methods across standard metrics while providing high-quality textured reconstruction across diverse pose and appearance, with a maximum speed of 12 FPS.