Chenxin Li

I am a Ph.D. student at The Chinese University of Hong Kong, advised by Prof. Yixuan Yuan. I received my M.Eng from Xiamen University under Prof. Xinghao Ding and Prof. Yue Huang, where I also earned my B.Eng.

My recent research focuses on 3D Visual Generation (Diffusion, 3DGS), Understanding (Visual Foundation Models) and Reasoning (Vision Language Models, Agents). Welcome to have a chat for potential collaboration and internship opportunities.

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Latest News

  • [03/2025] Four papers (Track Any Anomaly+EfficientSplat+FlexGS+JarvisIR) accepted to CVPR 2025.
  • [02/2025] One paper (InstantSplamp) accepted to ICLR 2025. See you in Sigapore to have a chat!
  • [01/2025] One paper (U-KAN) accepted to AAAI 2025.
  • [12/2025] One paper (ConcealGS) accepted to ICASSP 2025 and one paper (Hide-in-Motion) accepted to ICRA 2025.
  • [11/2024] One paper (EndoGaussian) accepted to TMI 2024.
  • [09/2024] One paper (Flaws can be Applause) accepted to NeurIPS 2024.
  • [09/2024] One paper (VLM Fine-tuning) accepted to EMNLP 2024.
  • [07/2024] One paper (P$^2$SAM) accepted to ACM MM 2024.
  • [07/2024] One paper (GTP-4o) accepted to ECCV 2024.
  • [06/2024] Three papers (Endora + EndoSparse + LGS) accepted to MICCAI 2024.
  • [07/2023] One paper (StegaNeRF) accepted to ICCV 2023.
Main Publications

For full publications, visit [Google Scholar].

U-KAN Makes Strong Backbone for Medical Image Segmentation and Generation
Chenxin Li*, Xinyu Liu*, Wuyang Li*, Cheng Wang*, Hengyu Liu, Yixuan Yuan
AAAI, 2025
[Project] [ArXiv] [Code]

The endeavours unveil valuable insights and sheds light on the prospect that with U-KAN, you can make strong backbone for medical image segmentation and generation.

InstantSplamp: Fast and Generalizable Stenography Framework for Generative Gaussian Splatting
Chenxin Li*, Hengyu Liu*, Zhiwen Fan, Wuyang Li, Yifan Liu, Panwang Pan, Yixuan Yuan
ICLR, 2025
[Project] [ArXiv] [ArXiv] [Code]

An initial exploration into embedding customizable, imperceptible, and recoverable information within the renders produced by off-the-line 3D generative models, while ensuring minimal impact on the rendered content's quality.

GTP-4o: Modality-prompted Heterogeneous Graph Learning for Omni-modal Biomedical Representation
Chenxin Li, Xinyu Liu*, Cheng Wang*, Yifan Liu, Weihao Yu, Jing Shao, Yixuan Yuan (* Equal Second-author Contribution)
ECCV, 2024
[Project] [ArXiv] [Code]

A pioneering foray into the intriguing realm of embedding, relating and perceiving the heterogeneous patterns from various biomedical modalities holistically via a graph theory. An pioneering foray into the intriguing realm of embedding, relating and perceiving the heterogeneous patterns from various biomedical modalities holistically via a graph theory.

Endora: Video Generation Models as Endoscopy Simulators
Chenxin Li*, Hengyu Liu*, Yifan Liu*, Brandon Y. Feng, Wuyang Li, Xinyu Liu, Zhen Chen, Jing Shao, Yixuan Yuan (* Equal Contribution)
MICCAI, 2024
[Project] [ArXiv] [Video] [Code]

A pioneering exploration into high-fidelity medical video generation on endoscopy scenes

EndoGaussian: Gaussian Splatting for Deformable Surgical Scene Reconstruction
Yifan Liu*, Chenxin Li*, Chen Yang, Yixuan Yuan (* Equal Contribution)
TMI, 2024
[Project] [ArXiv] [Video] [Code]

Real-time surgical reconstruction with Gaussian Splatting representation

StegaNeRF: Embedding Invisible Information within Neural Radiance Fields
Chenxin Li*, Brandon Y. Feng*, Zhiwen Fan*, Panwang Pan, Zhangyang Wang (* Equal Contribution)
International Conference on Computer Vision (ICCV), 2023
[Project] [ArXiv] [Video] [Code]

NeRF with multi-modal IP information instillation

Knowledge Condensation Distillation
Chenxin Li, Mingbao Lin, Zhiyuan Ding, Nie Lin, Yihong Zhuang, Xinghao Ding, Yue Huang, Liujuan Cao
European Conference on Computer Vision (ECCV), 2022
[PDF] [Supp] [ArXiv] [Code]

Co-design of dataset and model distillation


Professional Activities

Conference Reviewer

ICLR, NeurIPS, ICML, CVPR, ICCV, ECCV, EMNLP, AAAI, ACM MM, MICCAI, BIBM (and more)

Journal Reviewer

TIP, DMLR, PR, TNNLS, NCA (and more)


Modified from Jon Barron