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Yingyan Xu

4 accepted papers

2026

RelightAnyone: A Generalized Relightable 3D Gaussian Head Model

CVPR 2026

3D Gaussian Splatting (3DGS) has become a standard approach to reconstruct and render photorealistic 3D head avatars. A major challenge is to relight the avatars to match any scene illumination. For high quality relighting, existing methods require subjects to be captured under complex time-multiple

Cited by 0SourceScholar
2025

Monocular Facial Appearance Capture in the Wild

ICCV 2025poster

We present a new method for reconstructing the appearance properties of human faces from a lightweight capture procedure in an unconstrained environment. Our method recovers the surface geometry, diffuse albedo, specular intensity and specular roughness from a monocular video containing a simple hea…

Cited by 0SourcePDFScholar
2024

Artist-Friendly Relightable and Animatable Neural Heads

CVPR 2024poster

An increasingly common approach for creating photo-realistic digital avatars is through the use of volumetric neural fields. The original neural radiance field (NeRF) allowed for impressive novel view synthesis of static heads when trained on a set of multi-view images and follow up methods showed t…

Cited by 4SourcePDFScholar
2023

ReNeRF: Relightable Neural Radiance Fields with Nearfield Lighting

ICCV 2023poster

Recent work on radiance fields and volumetric inverse rendering (e.g., NeRFs) has provided excellent results in building data-driven models of real scenes for novel view synthesis with high photorealism. While full control over viewpoint is achieved, scene lighting is typically "baked" into the mode…

Cited by 21PDFScholar