Generative Relightable Avatars

• URL: http://arxiv.org/abs/2606.22718v1
• Date: Sun, 21 Jun 2026 23:36:00 GMT
• Title: Generative Relightable Avatars
• Abstract summary: Generative Relightable Avatars (GRA) is a person-specific method for free-view rendering and environment-map relighting of full-body humans.<n>GRA follows a hybrid approach that combines controllable, physics-grounded relighting with probabilistic refinement.
• Score: 54.38436795769187
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present Generative Relightable Avatars (GRA), a person-specific method for photorealistic free-view rendering and environment-map relighting of full-body humans. We postulate that modeling fine-grained appearance details is inherently a one-to-many problem that can benefit from a generative formulation. In contrast to fully regressive relightable avatar methods, GRA follows a hybrid approach that combines controllable, physics-grounded relighting with probabilistic refinement. Starting from a tracked animated mesh, we optimize material parameters in UV-space and render a coarse relit appearance under a target HDR environment map. Next, we refine the textures with a feed-forward model to capture pose-dependent texture dynamics and illumination effects beyond simplified reflectance assumptions. Finally, a fine-tuned video-to-video diffusion model transforms the physically grounded renderings into temporally coherent, high-detail videos while preserving 3D control, with an error-recycling strategy for generating long videos. Experimental evaluations demonstrate our method's improved perceptual quality over prior relightable avatar baselines. Project Page: https://vcai.mpi-inf.mpg.de/projects/GRA/

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