TriHuman : A Real-time and Controllable Tri-plane Representation for Detailed Human Geometry and Appearance Synthesis

• URL: http://arxiv.org/abs/2312.05161v1
• Date: Fri, 8 Dec 2023 16:40:38 GMT
• Title: TriHuman : A Real-time and Controllable Tri-plane Representation for Detailed Human Geometry and Appearance Synthesis
• Authors: Heming Zhu, Fangneng Zhan, Christian Theobalt, Marc Habermann
• Abstract summary: TriHuman is a novel human-tailored, deformable, and efficient tri-plane representation. We non-rigidly warp global ray samples into our undeformed tri-plane texture space. We show how such a tri-plane feature representation can be conditioned on the skeletal motion to account for dynamic appearance and geometry changes.
• Score: 76.73338151115253
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Creating controllable, photorealistic, and geometrically detailed digital doubles of real humans solely from video data is a key challenge in Computer Graphics and Vision, especially when real-time performance is required. Recent methods attach a neural radiance field (NeRF) to an articulated structure, e.g., a body model or a skeleton, to map points into a pose canonical space while conditioning the NeRF on the skeletal pose. These approaches typically parameterize the neural field with a multi-layer perceptron (MLP) leading to a slow runtime. To address this drawback, we propose TriHuman a novel human-tailored, deformable, and efficient tri-plane representation, which achieves real-time performance, state-of-the-art pose-controllable geometry synthesis as well as photorealistic rendering quality. At the core, we non-rigidly warp global ray samples into our undeformed tri-plane texture space, which effectively addresses the problem of global points being mapped to the same tri-plane locations. We then show how such a tri-plane feature representation can be conditioned on the skeletal motion to account for dynamic appearance and geometry changes. Our results demonstrate a clear step towards higher quality in terms of geometry and appearance modeling of humans as well as runtime performance.

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