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20242026
most citedRelightAnyone: A Generalized Relightable 3D Gaussian Head Model

1 citations · 1 across the 1 of their papers we have counts for

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7 papers

cs.CV20261 cited

RelightAnyone: A Generalized Relightable 3D Gaussian Head Model

Yingyan Xu, Pramod Rao, Sebastian Weiss +5

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…

cs.CV2026

FastGHA: Generalized Few-Shot 3D Gaussian Head Avatars with Real-Time Animation

Xinya Ji, Sebastian Weiss, Manuel Kansy +4

Despite recent progress in 3D Gaussian-based head avatar modeling, efficiently generating high fidelity avatars remains a challenge. Current methods typically rely on extensive mul…

cs.CV2025

Multimodal Conditional 3D Face Geometry Generation

Christopher Otto, Prashanth Chandran, Sebastian Weiss +3

We present a new method for multimodal conditional 3D face geometry generation that allows user-friendly control over the output identity and expression via a number of different c…

cs.CV2025

Monocular Facial Appearance Capture in the Wild

Yingyan Xu, Kate Gadola, Prashanth Chandran +4

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 su…

cs.GR2025

ScaffoldAvatar: High-Fidelity Gaussian Avatars with Patch Expressions

Shivangi Aneja, Sebastian Weiss, Irene Baeza +4

Generating high-fidelity real-time animated sequences of photorealistic 3D head avatars is important for many graphics applications, including immersive telepresence and movies. Th…

cs.CV2025

Joint Learning of Depth and Appearance for Portrait Image Animation

Xinya Ji, Gaspard Zoss, Prashanth Chandran +4

2D portrait animation has experienced significant advancements in recent years. Much research has utilized the prior knowledge embedded in large generative diffusion models to enha…