activity
20202026
most citedFully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernels

47 citations · 50 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026★ 1 cited

GeoRelight: Learning Joint Geometrical Relighting and Reconstruction with Flexible Multi-Modal Diffusion Transformers

Yuxuan Xue, Ruofan Liang, Egor Zakharov +6

Relighting a person from a single photo is an attractive but ill-posed task, as a 2D image ambiguously entangles 3D geometry, intrinsic appearance, and illumination. Current method…

cs.CV2024

URHand: Universal Relightable Hands

Zhaoxi Chen, Gyeongsik Moon, Kaiwen Guo +20

Existing photorealistic relightable hand models require extensive identity-specific observations in different views, poses, and illuminations, and face challenges in generalizing t…

cs.CV2022★ 1 cited

NeuWigs: A Neural Dynamic Model for Volumetric Hair Capture and Animation

Ziyan Wang, Giljoo Nam, Tuur Stuyck +6

The capture and animation of human hair are two of the major challenges in the creation of realistic avatars for the virtual reality. Both problems are highly challenging, because…

cs.CV2021★ 1 cited

High-fidelity Face Tracking for AR/VR via Deep Lighting Adaptation

Lele Chen, Chen Cao, Fernando De la Torre +3

3D video avatars can empower virtual communications by providing compression, privacy, entertainment, and a sense of presence in AR/VR. Best 3D photo-realistic AR/VR avatars driven…

cs.CV2020★ 47 cited

Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernels

Yi Zhou, Chenglei Wu, Zimo Li +5

Learning latent representations of registered meshes is useful for many 3D tasks. Techniques have recently shifted to neural mesh autoencoders. Although they demonstrate higher pre…