Wuyang LI
I am a Research Scientist (since Feb 2025) at the VITA
(Visual Intelligence for Transportation) Lab at EPFL (Γcole
Polytechnique FΓ©dΓ©rale de Lausanne). I feel
extremely fortunate to work under the supervision of Prof. Alexandre Alahi.
My research focuses on autonomous mobility and robotics, as well as developing innovative computer
vision and machine learning solutions.
Before this, I worked as a Postdoctoral Researcher (2024β2025) at the Chinese University of Hong
Kong (CUHK) and
completed my PhD (2020β2023) at the City University of Hong Kong (CityUHK) with Early Graduation. During my PhD, I focused on
visual perception in the context of autonomous driving, thoroughly addressing two-dimensional
challenges posed by out-of-distribution data and domain shifts. I was also fortunate to have had the
opportunity to work with Prof. Bo Han. I
completed my undergraduate studies (2016β2020) at Tianjin University.
I am open to research collaborations. If you are interested in my previous work, please don't
hesitate to contact me.
Email  / 
CV  / 
Google Scholar
 / 
Github
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π₯ News
- [03-2025] 1 co-authored papers about LLM is accepted by TMI 2025!
Thanks to all the co-authors!
- [02-2025] 2 co-authored papers (FlexGS and TAO) are accepted by CVPR 2025!
Thanks to all the co-authors!
- [01-2025] 2 co-authored papers (InstantSplamp and PDH-Diffusion) are accepted by ICLR
2025! Thanks to all the co-authors!
- [01-2025] 1 co-authored paper (Hide-In-Motion) is accpectd by ICRA 2025! Thanks
to all the co-authors!
- [12-2024] 2 co-authored papers (U-KAN and DPA) are accepted by AAAI 2025!
Thanks to all the co-authors!
- [12-2024] 1 co-authored paper on 3D GS watermarking has been accepted by ICASSP
2025!
- [11-2024] 1 co-authored paper about MRI phenotype prediction foundation model is accepted by
TMI 2024! Contracts to Zhibin!
- [10-2024] I am selected as the Top Reviewer at
NeurIPS 2024!
- [09-2024] 1 paper about SAM for uncertainty modeling is accepted by NeurIPS
2024. Congrats to Chenxin!
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[Milestone] From 08/2021 to 08/2024, my first-author works have been selected as
ORAL at 4 CV conferences: CVPR, ICCV,
ECCV, and AAAI!
- [08-2024] Our work CLIFF is selected as ORAL in ECCV
- [07-2024] We are organizing the first workshop on
multi-modal medical foundation models at NeurIPS; Submission
Link
- [07-2024] 1 paper using diffusion to tackle the open-vocabulary issue from a probabilistic
viewpoint is accepted by ECCV
2024
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[06-2024] 6 papers are accepted by MICCAI 2024 , including the works related
to:
Video Generation, Efficient Gaussian Splatting, 3D Point Cloud Segmentation,
Diffusion Model, and Brain Analysis.
- [04-2024] Our work on metasurfaces and stereo vision has been selected as the Cover Paper in ACS Photonics!
- [12-2023] I pass my PhD defense with Early
Graduation!!
- [08-2023] Our work SOMA is selected as ORAL in
ICCV.
- [07-2023] 2 papers are accepted by ICCV 2023.
- [06-2023]
Successfully secured seed funding for our startup team!
- [05-2023] 1 paper is accepted by MICCAI 2023.
- [04-2023] 1 paper is accepted by TNNLS 2023.
- [03-2023] 1 paper is accepted by TMI 2023.
- [02-2023] 1 paper is accepted by CVPR 2023.
- [01-2023] 1 paper is accepted by TPAMI 2023.
- [10-2022] 1 paper is accepted by TMM 2022.
- [06-2022] Our work SIGMA appears on CVPR Best Paper
Finalist
[33/8161]!
- [05-2022] 1 paper is accepted by MICCAI 2022 ( Early
Accept,
ORAL).
- [03-2022] 2 papers are accepted by CVPR 2022 (one
ORAL
).
- [10-2021] Our work SCAN is accepted by AAAI 2022 (
ORAL
).
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π Selected Publication
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VoxDet: Rethinking 3D Semantic Occupancy Prediction as Dense Object Detection
ArXiv Preprint, 2025
Wuyang Li, Zhuy Yu, Alexandre Alahi
project page
/
paper
/
codes (coming)
Key Words: 3D Semantic Occupancy Prediction; Dense Object Detection
TL;DR: VoxDet address semantic occupancy prediction with an instance-centric formulation inspried by dense object detection, which uses a VoxNT trick freely transferring voxel-level class labels to instance-level offset labels.
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CLIFF: Continual Latent Diffusion for Open-Vocabulary Object Detection
European Conference on Computer Vision, ECCV, 2024,
ORAL
Wuyang Li, Xinyu Liu, Jiayi Ma, Yixuan Yuan
paper
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codes
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video
Key Words: Open-Vocabulary Object Detection; Diffusion Model
TL;DR: A probabilistic pipeline modeling the subspace transfer among the object,
image, and text subspaces with continual diffusion.
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From Static to Dynamic Diagnostics: Boosting Medical Image Analysis via
Motion-Informed Generative Videos
Medical Image Computing and Computer Assisted Intervention, , MICCAI, 2024
Wuyang Li, Xinyu Liu, Qiushi Yang, Yixuan Yuan
paper
Key Words: Medical Video Generation; Semi-Supervised Diagnosis
TL;DR: Enhancing the semi-supervised diganosis with generative medical
videos, enabling the learning across image and video modalities jointly.
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When 3D Partial Points Meets SAM: Tooth Point Cloud Segmentation with Sparse
Labels
Medical Image Computing and Computer Assisted Intervention, , MICCAI, 2024
Yifan Liu, Wuyang Li, Cheng Wang, Hui Chen, Yixuan Yuan
paper
Key Words: SAM; 3D Point Cloud Segmentation; Severely Limited Label
TL;DR: Leveraging the SAM to address the severe label scarcity in 3D
point cloud segmentation, enbaling good perfromance with only 0.1% label ratio.
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Novel Scenes & Classes: Towards Adaptive Open-set Object Detection
IEEE International Conference on Computer Vision (ICCV), 2023,
ORAL
Wuyang Li, Xiaoqing Guo, Yixuan Yuan
paper
/
codes
Key Words: Open-Set/ Domain Adaptive Object Detection
TL;DR: Formulating a real-world friendly setting with
out-of-distribution
and domain shift, and addressing with high-order subgraphs.
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MRM: Masked Relation Modeling for Medical Image Pre-Training with
Genetics
IEEE International Conference on Computer Vision (ICCV), 2023
Qiushi Yang, Wuyang Li, Paul Li, Yixuan Yuan
paper
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codes
Key Words: Multimodal Pretraining; Masked Image Modeling
TL;DR: Observing the failure in MIM when the informative
foreground
is limited, and turning to masking relation to solve this issue.
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Adjustment and Alignment for Unbiased Open Set Domain Adaptation
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Wuyang Li, Jie Liu, Bo Han, Yixuan Yuan
paper
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codes/
video
Key Words: Open Set Domain Adaptation; Causal Theory
TL;DR: Driven by new observations, proposing a theoretically
grounded method to tackle biased learning and cross-domain transfer with
causality.
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SIGMA: Semantic-complete Graph Matching for Domain Adaptive Object
Detection
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022,
ORAL, Best Paper Finalist
Wuyang Li, Xinyu Liu, Yixuan Yuan
paper /
codes /
η₯δΉ
Key Words: Domain Adaptive Object Detection; Graph Matching
TL;DR: Reformulating domain adaptation as a graph matching
problem among fine-grained cross-domain feature points.
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Towards Robust Adaptive Object Detection under Noisy Annotations
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022
Xinyu Liu, Wuyang Li, Qiushi Yang, Baopu Li, Yixuan Yuan
paper /
codes
Key Words: Open Set Domain Adaptation; Noisy Label
TL;DR: Exploring a more practical setting with noisy
annotations
in DAOD and solving by measuring the latent transferability of object noise.
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SCAN: Cross Domain Object Detection with Semantic Conditioned
Adaptation
The Association for the Advance of Artificial Intelligence (AAAI), 2022,
ORAL
Wuyang Li, Xinyu Liu, Xiwen Yao, Yixuan Yuan
paper /
codes
Key Words: Open Set Domain Adaptation; Graph-based Learning
TL;DR: Discovering the key factor leading to the perforrmance
drop in DAOD and addressing with cross-domain semantic-conditioned kernels.
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Intervention & Interaction Federated Abnormality Detection with
Noisy
Clients
Medical Image Computing and Computer Assisted Intervention (MICCAI),
2022,
ORAL, Early Accept
Xinyu Liu, Wuyang Li, Yixuan Yuan
paper
/
codes
Key Words: Federated Learning; Noisy Label; Causal Theory
TL;DR: Studying the recognition bias in federated object
detection under noisy annotations, and addressing the bias with a novel causal
intervention.
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SIGMA++: Improved Semantic-complete Graph Matching for Domain
Adaptive Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI),
2023,
IF:
24.314
Wuyang Li, Xinyu Liu, Yixuan Yuan
paper /
codes
Key Words: Domain Adaptive Object Detection; Hypergraph
Matching
TL;DR: Improving pair-wise SIGMA with high-order hypergraph,
thereby addressing the domain misalignment with group-level adaptation.
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HTD: Heterogeneous Task Decoupling for Two-Stage Object Detection
IEEE Transactions on Image Processing (TIP), 2022, IF: 11.041
Wuyang Li, Zhen Chen, Baopu Li, Dingwen Zhang, Yixuan Yuan
paper
/
codes
Key Words: Generic Object Detection; Graph-based Learning
TL;DR: Discovering the heterogeneous feature demands between
the classification and regression, and solving via task-decoupled designs.
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Decoupled Unbiased Teacher for Source-Free Domain Adaptive Medical
Object
Detection
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Xinyu Liu, Wuyang Li, Yixuan Yuan
paper /
codes
Key Words: Source-free Domain Adaptive Object Detection;
Causal Theory
TL;DR: Identifying the bias at the data, model and prediction
levels in SFDA, and sovling with causal intervention.
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π Other Publication
Image/Video Generative Models
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Endora: Video Generation Models as Endoscopy
Simulators
Chenxin Li, Hengyu Liu, Yifan Liu, Brandom Feng, Wuyang
Li, Xinyu Liu, Zhen Chen, Jing Shao, Yixuan Yuan
Medical Image Computing and Computer Assisted Intervention (MICCAI),
2024
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DiffRect: Latent Diffusion Label Rectification for Semi-supervised
Medical Image Segmentation
Xinyu Liu, Wuyang Li, Yixuan Yuan
Medical Image Computing and Computer Assisted Intervention (MICCAI),
2024
Brain MRI Analysis
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FM-APP: Foundation Model for Any Phenotype Prediction via fMRI to
sMRI Knowledge Transfer
Zhibin He, Wuyang Li, Yifan Liu, Xinyu Liu, Junwei Han,
Tuo Zhang, Yixuan Yuan
IEEE Transactions on Medical Imaging (TMI), 2024, Under Review
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F2TNet: FMRI to T1w MRI Knowledge Transfer Network for Brain
Multi-phenotype Prediction
Zhibin He, Wuyang Li, Yu Jiang, Zhihao Peng, Pengyu Wang,
Xiang Li, Tianming Liu, Junwei Han, et al.
Medical Image Computing and Computer Assisted Intervention (MICCAI),
2024
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H2GM: A Hierarchical Hypergraph Matching Framework for Brain
Landmark Alignment
Zhibin He, Wuyang Li, Tuo Zhang, Yixuan Yuan
Medical Image Computing and Computer Assisted Intervention (MICCAI),
2023
LLM Agent
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LLM-guided Decoupled Probabilistic Prompt for Continual Learning
in Medical Image Diagnosis
Yiwen Luo, Wuyang Li, Chen Cheng, Xiang Li, Tianming Liu,
Yixuan Yuan
IEEE Transactions on Medical Imaging (TMI), 2024, Under Revision
3D Vision
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LGS: A Light-weight 4D Gaussian Splatting for Efficient Surgical
Scene Reconstruction
Hengyu Liuβ, Yifan Liuβ, Chenxin Liβ, Wuyang Li, Yixuan
Yuan
Medical Image Computing and Computer Assisted Intervention (MICCAI),
2024
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Stereo Vision Meta-Lens-Assisted Driving Vision
Xiaoyuan Liu, Wuyang Li, Takeshi Yamaguchi, Zihan Geng,
Takuo Tanaka, Din Ping Tsai, Mu Ku Chen
ACS Photonics, 2024, Selected as Cover Paper
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GRAB-Net: Graph-based Boundary-aware Network for Medical Point
Cloud Segmentation
Yifan Liu, Wuyang Li, Jie Liu, Hui Chen, Yixuan Yuan
IEEE Transactions on Medical Imaging (TMI), 2023
Graph-based Learning
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Medical Federated Learning with Joint Graph Purification for Noisy
Label Learning
Zhen Chen, Wuyang Li, Xiaohan Xing, Yixuan Yuan
IEEE Transactions on Neural Networks and Learning Systems (TNNLS),
2023
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SCAN++: Enhanced Semantic Conditioned Adaptation for Domain
Adaptive Object Detection
Wuyang Li, Xinyu Liu, Yixuan Yuan
IEEE Transactions on Multimedia (TMM), 2022
Medical Imaging Analysis
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U-KAN Makes Strong Backbone for Medical Image Segmentation and
Generation
Chenxin Liβ, Xinyu Liuβ, Wuyang Liβ, Cheng Wangβ, Hengyu
Liu, Yixuan Yuan (β Equal Contribution)
ArXiv preprint arXiv:2406.02918, 2024
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Joint polyp detection and segmentation with heterogeneous
endoscopic data
Wuyang Li, Chen Yang, Jie Liu, Xiaoqing Guo, Yixuan
Yuan
International Symposium on Biomedical Imaging (ISBI) Workshop,
2021
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π‘ Service
Journals Reviewer
- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
- International Journal of Computer Vision (IJCV)
- IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
- IEEE Transactions on Image Processing (TIP)
- IEEE Transactions on Automation Science and Engineering (TASE)
- Pattern Recognition (PR)
Conferences Reviewer
- Conference on Neural Information Processing Systems (neurIPS), 2024
- IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023, 2024
- IEEE International Conference on Computer Vision (ICCV), 2023
- AAAI Conference on Artificial Intelligence (AAAI), 2023, 2024
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π
Selected Honors
- [2023] Outstanding Academic Performance Award (OAPA), CityU
- [2023] Research Tuition Scholarship (RTS), CityU
- [2022] Outstanding Academic Performance Award (OAPA), CityU
- [2022] Research Tuition Scholarship (RTS), CityU
- [2018] National Scholarship (Top 2% student)
- [2017] National Scholarship (Top 2% student)
- [2017] Tianjin Mathematical Competition (Second Prize)
- [2017-2020] Outstanding Student Scholarship (Top 10% student)
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Tianjin University (TJU), China
Sep. 2016 - Jun. 2020οΌ Bachelor's degree of Communication Engineering.
GPA: 3.83/4.00, 91.3/100, Ranking 6/120
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NUS (Suzhou) Research Institute (NUSRI), China
Sep. 2019 - Jun. 2020: Exchanging program of Electrical and Computer
Engineering.
Supervisors: Prof. Zhiying Zhou
Complete the project: Towards Webpage-based Augmentation Reality (AR)
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City University of Hong Kong (CityU), China
Sep. 2020 - Dec. 2023: Ph.D Study of Electrical Engineering.
Supervisors: Prof. Yixuan Yuan
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Founder & Director, ScholaGO Education Technology Company Limited
To gain a deeper understanding of technology, I founded
ScholaGO Education Technology Company Limited
(εΈζ
ιζθ²η§ζζιε
¬εΈ) with four co-founders to develop
an innovative educational product aimed at converting static knowledge into an immersive,
interactive, multi-modal adventure. Our company is supported by HKSTP, HK Tech 300, and Alibaba Cloud.
My ultimate goal is to develop valuable technologies and products to improve the national happiness
index.
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π¨ Personal Interests
- Painting and Designing: I used to do sketch training with art
candidates
and
have a
a certain level of graphic design foundation. I have a strong
interest
in user
needs
analysis and product design.
- I am looking for the opportunity to establish a start-up team
and
create
some
awesome high-tech products.
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