Fangyin Weifwei@princeton.edu I am a research scientist in the Deep Imagination Research Group at NVIDIA. My research lies at the intersection of computer vision, computer graphics, and machine learning. I am currently interested in 3D modeling, synthesis, and editing through the lens of machine learning. I received my Ph.D. at Princeton University, where I was co-advised by Szymon Rusinkiewicz and Thomas Funkhouser. Prior to joining Princeton, I got my Bachelor's in Computer Science and Economy from Peking University. I was a research intern at Meta Reality Labs, Uber ATG R&D, Google Research, Microsoft Research Asia, and Stanford University. / |
@inproceedings{chen:2024:vcrgaus, author = "Hanlin Chen and Fangyin Wei and Chen Li and Tianxing Huang and Yunsong Wang and Gim Hee Lee", title = "VCR-GauS: View Consistent Depth-Normal Regularizer for Gaussian Surface Reconstruction", booktitle = "Advances in Neural Information Processing Systems", year = "2024" } |
@inproceedings{duan:2024:4drotorgs, author = "Yuanxing Duan and Fangyin Wei and Qiyu Dai and Yuhang He and Wenzheng Chen and Baoquan Chen", title = "4D-Rotor Gaussian Splatting: Towards Efficient Novel-View Synthesis for Dynamic Scenes", booktitle = "Proc. SIGGRAPH", year = "2024", month = July } |
@inproceedings{Wei:2023:CDA, author = "Fangyin Wei and Thomas Funkhouser and Szymon Rusinkiewicz", title = "Clutter Detection and Removal in {3D} Scenes with View-Consistent Inpainting", booktitle = "International Conference on Computer Vision (ICCV)", year = "2023", month = oct } |
@InProceedings{Zhang_2023_ICCV, author = {Zhang, Xiang and Chen, Zeyuan and Wei, Fangyin and Tu, Zhuowen}, title = {Uni-3D: A Universal Model for Panoptic 3D Scene Reconstruction}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, month = {October}, year = {2023}, pages = {9256-9266} } |
@inproceedings{wei2022nasam, title = {Self-supervised Neural Articulated Shape and Appearance Models}, author = {Fangyin Wei and Rohan Chabra and Lingni Ma and Christoph Lassner and Michael Zollhoefer and Szymon Rusinkiewicz and Chris Sweeney and Richard Newcombe and Mira Slavcheva}, booktitle = {Proceedings IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, year={2022} } |
@inproceedings{Wei:2020:LTI, author = "Fangyin Wei and Elena Sizikova and Avneesh Sud and Szymon Rusinkiewicz and Thomas Funkhouser", title = "Learning to Infer Semantic Parameters for {3D} Shape Editing", booktitle = "International Conference on 3D Vision (3DV)", year = "2020", month = nov } |
Learned Feature Embeddings for Non-Line-of-Sight Imaging and RecognitionWenzheng Chen*, Fangyin Wei*, Kyros Kutulakos, Szymon Rusinkiewicz, Felix HeideACM Transactions on Graphics (Proc. SIGGRAPH Asia), 2020  
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@article{Chen:NLOS:2020, title = {Learned Feature Embeddings for Non-Line-of-Sight Imaging and Recognition}, author = {Wenzheng Chen and Fangyin Wei and Kiriakos N. Kutulakos and Szymon Rusinkiewicz and Felix Heide}, year = {2020}, issue_date = {December 2020}, publisher = {Association for Computing Machinery}, volume = {39}, number = {6}, journal = {ACM Transactions on Graphics (Proc. SIGGRAPH Asia)}, } |
Seeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler RadarNicolas Scheiner*, Florian Kraus*, Fangyin Wei*, Buu Phan, Fahim Mannan, Nils Appenrodt, Werner Ritter, Jürgen Dickmann, Klaus Dietmayer, Bernhard Sick, Felix HeideComputer Vision and Pattern Recognition (CVPR), 2020  
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@InProceedings{scheiner2019seeing, author={Scheiner, Nicolas and Kraus, Florian and Wei, Fangyin and Phan, Buu and Mannan, Fahim and Appenrodt, Nils and Ritter, Werner and Dickmann, J{\"u}rgen and Dietmayer, Klaus and Sick, Bernhard and Heide, Felix}, title={Seeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar}, booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2020} } |
ADA-Tucker: Compressing deep neural networks via adaptive dimension adjustment tucker decompositionZhisheng Zhong, Fangyin Wei, Zhouchen Lin, Chao ZhangNeural Networks 110: 104-115, 2019  
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@article{DBLP:journals/nn/ZhongWLZ19, author = {Zhisheng Zhong and Fangyin Wei and Zhouchen Lin and Chao Zhang}, title = {ADA-Tucker: Compressing deep neural networks via adaptive dimension adjustment tucker decomposition}, journal = {Neural Networks}, volume = {110}, pages = {104--115}, year = {2019}, url = {https://doi.org/10.1016/j.neunet.2018.10.016}, } |
Integral Human Pose RegressionXiao Sun, Bin Xiao, Fangyin Wei, Shuang Liang, Yichen WeiEuropean Conference of Computer Vision (ECCV), 2018   |
Exploring Disentangled Feature Representation Beyond Face IdentificationYu Liu*, Fangyin Wei*, Jing Shao*, Lu Sheng, Junjie Yan, Xiaogang WangComputer Vision and Pattern Recognition (CVPR), 2018   |
Recurrent Scale Approximation for Object Detection in CNNYu Liu, Hongyang Li , Junjie Yan, Fangyin Wei, Xiaogang Wang, Xiaoou TangInternational Conference of Computer Vision (ICCV), 2017   |
Teaching Assistant
Princeton University COS 526: Neural Rendering, Spring 2023
Princeton University COS 302: Mathematics for Numerical Computing and Machine Learning, Fall 2020
Princeton University COS 302: Mathematics for Numerical Computing and Machine Learning, Spring 2020
Princeton University COS 429: Computer Vision, Fall 2019
Web design stolen from Jon Barron