Generalizable Neural Human Renderer

arXiv:2404.14199v1 Announce Type: new
Abstract: While recent advancements in animatable human rendering have achieved remarkable results, they require test-time optimization for each subject which can be a significant limitation for real-world applications. To address this, we tackle the challenging task of learning a Generalizable Neural Human Renderer (GNH), a novel method for rendering animatable humans from monocular video without any test-time optimization. Our core method focuses on transferring appearance information from the input video to the output image plane by …

abstract applications arxiv cs.cv human humans novel optimization rendering results test type world