activity
20232026
collaborators

5 papers

cs.CV2026

Large-scale Codec Avatars: The Unreasonable Effectiveness of Large-scale Avatar Pretraining

Junxuan Li, Rawal Khirodkar, Chengan He +37

High-quality 3D avatar modeling faces a critical trade-off between fidelity and generalization. On the one hand, multi-view studio data enables high-fidelity modeling of humans wit…

cs.CV2026

Omni123: Exploring 3D Native Foundation Models with Limited 3D Data by Unifying Text to 2D and 3D Generation

Chongjie Ye, Cheng Cao, Chuanyu Pan +4

Recent multimodal large language models have achieved strong performance in unified text and image understanding and generation, yet extending such native capability to 3D remains…

cs.GR2025

3DGH: 3D Head Generation with Composable Hair and Face

Chengan He, Junxuan Li, Tobias Kirschstein +7

We present 3DGH, an unconditional generative model for 3D human heads with composable hair and face components. Unlike previous work that entangles the modeling of hair and face, w…

cs.CV2025

LUCAS: Layered Universal Codec Avatars

Di Liu, Teng Deng, Giljoo Nam +6

Photorealistic 3D head avatar reconstruction faces critical challenges in modeling dynamic face-hair interactions and achieving cross-identity generalization, particularly during e…

cs.CV2023

A Local Appearance Model for Volumetric Capture of Diverse Hairstyle

Ziyan Wang, Giljoo Nam, Aljaz Bozic +4

Hair plays a significant role in personal identity and appearance, making it an essential component of high-quality, photorealistic avatars. Existing approaches either focus on mod…