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Gaspard Zoss

7 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
2021

Adaptive Convolutions for Structure-Aware Style Transfer

CVPR 2021poster

Style transfer between images is an artistic application of CNNs, where the 'style' of one image is transferred onto another image while preserving the latter's content. The state of the art in neural style transfer is based on Adaptive Instance Normalization (AdaIN), a technique that transfers the…

Cited by 81PDFScholar