I received my Ph.D. degree in Computer Science and Technology from Zhejiang University in 2026, where I was advised by Prof. Xiaogang Jin. I received my B.S. degree from Chu Kochen College, Zhejiang University, in 2021. In 2025, I interned at the Codec Avatars Lab, Meta, working with Junxuan Li. From 2024 to 2025, I was an academic guest at the Computer Vision and Learning Group, ETH Zürich.
Outside of research, I enjoy painting.
I am always happy to explore potential collaborations. Feel free to get in touch via email.
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Codec Avatars Lab, Meta
Research Scientist InternJun. 2025 - Dec. 2025 -
ETH Zürich
Computer Vision and Learning Group
Academic GuestMay. 2024 - April. 2025
// education
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Zhejiang University
State Key Lab of CAD&CG
Ph.D. in Computer Science and Technology2021 - 2026 -
Zhejiang University
B.S. in Computer Science and Technology2017 - 2021
// research overview
My doctoral research has focused on the generation and editing of high-quality, realistic digital humans, spanning 2D portraits, static and dynamic digital humans, and large-scale multi-modal model training.
I am now expanding this line of research toward broader questions in generative modeling, world models, and emerging directions in AI.
// selected publications view all →
GenLCA: 3D Diffusion for Full-Body Avatars from In-the-Wild Videos
Yiqian Wu; Rawal Khirodkar; Egor Zakharov; Timur Bagautdinov; Lei Xiao; Zhaoen Su; Shunsuke Saito; Xiaogang Jin; Junxuan Li.
European Conference on Computer Vision (ECCV) 2026 Work was done during an internship at Meta
A diffusion-based generative model for generating and editing photorealistic full-body avatars from text and image inputs.
Text-based Animatable 3D Avatars with Morphable Model Alignment
Yiqian Wu; Malte Prinzler; Xiaogang Jin†; Siyu Tang.
ACM SIGGRAPH (Conference Track) 2025 Work was done during visiting ETH Zurich
A novel framework, AnimPortrait3D, for text-based realistic animatable 3DGS avatar generation with morphable model alignment.
3DPortraitGAN: Learning Canonical Full-Head 3D GANs from a Single-View Portrait Dataset with Diverse Body Poses
Yiqian Wu; Hao Xu; Xiangjun Tang; Yue Shangguan; Hongbo Fu; Xiaogang Jin†.
IEEE Transactions on Circuits and Systems for Video Technology 2025
The first 3D-aware one-quarter headshot portrait generator that learns a canonical 3D avatar distribution from the 360°PHQ dataset with body pose self-learning.
Portrait3D: Text-Guided High-Quality 3D Portrait Generation Using Pyramid Representation and GANs Prior
Yiqian Wu; Hao Xu; Xiangjun Tang; Xien Chen; Siyu Tang; Zhebin Zhang; Chen Li; Xiaogang Jin†.
ACM Transactions on Graphics (Proceedings of SIGGRAPH) 2024
A novel neural rendering-based framework with a novel joint geometry-appearance prior to achieve text-to-3D-portrait generation.
LPFF: A Portrait Dataset for Face Generators Across Large Poses
Yiqian Wu; Jing Zhang; Hongbo Fu; Xiaogang Jin†.
IEEE/CVF International Conference on Computer Vision (ICCV) 2023
A large-pose Flickr face dataset comprised of 19,590 high-quality real large-pose portrait images.
HairMapper: Removing Hair from Portraits Using GANs
Yiqian Wu; Yongliang Yang; Xiaogang Jin†.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022
A dataset and a baseline method for removing hair from portrait images using generative adversarial networks (GANs).
Coarse-to-Fine: Facial Structure Editing of Portrait Images via Latent Space Classifications
Yiqian Wu; Yongliang Yang; Qinjie Xiao; Xiaogang Jin†.
ACM Transactions on Graphics (Proceedings of SIGGRAPH) 2021
A novel method that can automatically remove the double chin effect in portrait images.