IntrinsicAvatar: Physically Based Inverse Rendering of Dynamic Humans from Monocular Videos via Explicit Ray Tracing
Shaofei Wang, Bo\v{z}idar Anti\'c, Andreas Geiger, Siyu Tang

TL;DR
IntrinsicAvatar is a novel method that explicitly models secondary shading effects via ray tracing to recover detailed, disentangled intrinsic properties of clothed human avatars from monocular videos, enabling realistic rendering and animation.
Contribution
It introduces an explicit ray tracing approach for inverse rendering of clothed humans from monocular videos, improving disentanglement and generalization to new poses and lighting.
Findings
High-quality geometry, albedo, material, and lighting recovered from monocular videos.
Explicit ray tracing improves disentanglement over neural-only methods.
Model generalizes well to novel poses and lighting conditions.
Abstract
We present IntrinsicAvatar, a novel approach to recovering the intrinsic properties of clothed human avatars including geometry, albedo, material, and environment lighting from only monocular videos. Recent advancements in human-based neural rendering have enabled high-quality geometry and appearance reconstruction of clothed humans from just monocular videos. However, these methods bake intrinsic properties such as albedo, material, and environment lighting into a single entangled neural representation. On the other hand, only a handful of works tackle the problem of estimating geometry and disentangled appearance properties of clothed humans from monocular videos. They usually achieve limited quality and disentanglement due to approximations of secondary shading effects via learned MLPs. In this work, we propose to model secondary shading effects explicitly via Monte-Carlo ray…
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Taxonomy
Topics3D Shape Modeling and Analysis · Advanced Vision and Imaging · Computer Graphics and Visualization Techniques
