Yujin Chen 陈雨劲

I am a final-year Ph.D. candidate in the Visual Computing Lab at the Technical University of Munich, supervised by Prof. Matthias Nießner. I am currently a Research Scientist Intern at Meta Reality Labs in Zurich. I received my B.Eng. and M.Sc. from Wuhan University.

I am seeking a full-time position, with an anticipated start in early 2027.

My research focuses on learning to represent, understand, and generate the dynamic 3D world. My work spans 3D appearance modeling, 3D/4D representation learning, and human interaction. I am interested in developing, adapting, and applying foundation models for spatial intelligence and generative world modeling.

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Experience

Research Scientist Intern, Meta Reality Labs, Zurich, Switzerland, Aug. 2026 – present

Research Scientist Intern, Meta Reality Labs, Redmond, United States, Jul. 2025 – Nov. 2025

Research Intern, Tencent AI Lab, Shenzhen, China, Dec. 2019 – Jun. 2021

Visiting Researcher, State University of New York at Buffalo, Buffalo, United States, Jul. 2019 – Nov. 2019

Research Assistant, Wuhan University, Wuhan, China, Jan. 2017 – Jun. 2021

Publications

Seen2Scene: Completing Realistic 3D Scenes with Visibility-Guided Flow

Quan Meng, Yujin Chen, Lei Li, Matthias Nießner, Angela Dai

European Conference on Computer Vision (ECCV), 2026

Completing realistic 3D scenes with visibility-guided flow matching learned directly from incomplete real-world scans.

Paper Code Video Project Page

Flowing from Reasoning to Motion: Learning 3D Hand Trajectory Prediction from Egocentric Human Interaction Videos

Mingfei Chen, Yifan Wang, Zhengqin Li, Homanga Bharadhwaj, Yujin Chen, Chuan Qin, Ziyi Kou, Yuan Tian, Eric Whitmire, Rajinder Sodhi, Hrvoje Benko, Eli Shlizerman, Yue Liu

European Conference on Computer Vision (ECCV), 2026

Connecting vision-language reasoning with motion generation to predict interaction-aware 3D hand trajectories from egocentric videos.

Paper Video Project Page Code

PBR-SR: Mesh PBR Texture Super Resolution from 2D Image Priors

Yujin Chen, Yinyu Nie, Benjamin Ummenhofer, Reiner Birkl, Michael Paulitsch, Matthias Nießner

Neural Information Processing Systems (NeurIPS), 2025

Enhancing mesh PBR textures with pretrained 2D super-resolution priors and multi-view differentiable rendering, without additional training.

Paper Code Video Project Page

Mesh2NeRF: Direct Mesh Supervision for Neural Radiance Field Representation and Generation

Yujin Chen, Yinyu Nie, Benjamin Ummenhofer, Reiner Birkl, Michael Paulitsch, Matthias Müller, Matthias Nießner

European Conference on Computer Vision (ECCV), 2024

Deriving radiance fields directly from textured meshes to supervise neural scene representations and 3D generation.

Paper Video Project Page

SSR-2D: Semantic 3D Scene Reconstruction from 2D Images

Junwen Huang, Alexey Artemov, Yujin Chen, Shuaifeng Zhi, Kai Xu, Matthias Nießner

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024

Completing 3D scene geometry, color, and semantics from RGB-D observations using 2D supervision and differentiable rendering.

Paper

PHRIT: Parametric Hand Representation with Implicit Template

Zhisheng Huang*, Yujin Chen*, Di Kang, Jinlu Zhang, Zhigang Tu (* equal contribution)

International Conference on Computer Vision (ICCV), 2023

Combining an implicit hand template with parametric deformation to model detailed, articulated hand geometry.

Paper

Consistent 3D Hand Reconstruction in Video via Self-supervised Learning

Zhigang Tu*, Zhisheng Huang*, Yujin Chen†, Di Kang, Linchao Bao, Bisheng Yang, Junsong Yuan (* equal contribution)(† senior authorship)

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023

Learning 3D hand reconstruction from monocular video with motion, shape, and texture consistency, without 3D annotations.

Paper Pdf Code

4DContrast: Contrastive Learning with Dynamic Correspondences for 3D Scene Understanding

Yujin Chen, Matthias Nießner, Angela Dai

European Conference on Computer Vision (ECCV), 2022

Learning transferable 3D scene features through contrastive pretraining with synthetic object motion and dynamic correspondences.

Paper Video Project Page

MixSTE: Seq2seq Mixed Spatio-Temporal Encoder for 3D Human Pose Estimation in Video

Jinlu Zhang, Zhigang Tu, Jianyu Yang, Yujin Chen, Junsong Yuan

Conference on Computer Vision and Pattern Recognition (CVPR), 2022

Estimating 3D human pose sequences from 2D joints by alternating spatial and temporal attention across video frames.

Paper Video Code

Model-based 3D Hand Reconstruction via Self-Supervised Learning

Yujin Chen, Zhigang Tu, Di Kang, Linchao Bao, Ying Zhang, Xuefei Zhe, Ruizhi Chen, Junsong Yuan

Conference on Computer Vision and Pattern Recognition (CVPR), 2021

Reconstructing hand pose, shape, and texture from a single RGB image using self-supervision from detected 2D keypoints and image appearance.

Paper Code Video Project Page

I2UV-HandNet: Image-to-UV Prediction Network for Accurate and High-fidelity 3D Hand Mesh Modeling

Ping Chen, Yujin Chen, Dong Yang, Fangyin Wu, Qin Li, Qingpei Xia, Yong Tan

International Conference on Computer Vision (ICCV), 2021

Reconstructing detailed 3D hand meshes from RGB images by predicting and super-resolving UV position maps.

Paper

Joint Hand-Object 3D Reconstruction from a Single Image with Cross-branch Feature Fusion

Yujin Chen, Zhigang Tu, Di Kang, Linchao Bao, Ruizhi Chen, Zhengyou Zhang, Junsong Yuan

IEEE Transactions on Image Processing (TIP), 2021

Jointly reconstructing hands and objects from a single image by sharing features between their reconstruction branches.

Paper arXiv

SO-HandNet: Self-Organizing Network for 3D Hand Pose Estimation with Semi-supervised Learning

Yujin Chen, Zhigang Tu, Liuhao Ge, Dejun Zhang, Ruizhi Chen, Junsong Yuan

International Conference on Computer Vision (ICCV), 2019

Learning 3D hand pose from labeled and unlabeled point clouds through joint pose estimation and point cloud reconstruction.

Paper Code

Services

Workshops

1st Workshop on Generating Digital Twins from Images and Videos, ICCV 2025 Workshop, Co-organizer

Reviewing

CVPR, ECCV, ICCV, NeurIPS, AAAI, TPAMI, IJCV, TIP

Teaching

Introduction to Deep Learning (IN2346), Head Teaching Assistant, 2022–2026. Course with more than 1,000 students.
Machine Learning for 3D Geometry (IN2392), Teaching Assistant, Summer 2022
Advanced Deep Learning for Computer Vision: Visual Computing (IN2390), Teaching Assistant, Winter 2021

Misc

Beyond academia, I enjoy exploring the world and capturing moments. Feel free to chat with me about sports 🧗 (I'm into bouldering and tennis), travel ✈️ , photography 📸 (my Flickr album), or any other interesting topics.