Xiefan Guo
Portrait of Xiefan Guo

I am a Ph.D. student in Computer Science at Beihang University (BUAA),
where I am advised by Prof. Di Huang.

My research interests are in computer vision and generative models, especially diffusion-based image and video generation.

I received my M.S. from Beihang University in 2023 and my B.E. from Tianjin University in 2020. I have interned at Shanghai AI Laboratory, Alibaba TongYi Lab, and Alibaba DAMO Academy.

Open to Opportunities:I expect to graduate in December 2026 and am currently on the job market for research positions in academia and industry, particularly in image/video generation and world models.

News

  • Jun 2026
    Our paper, titled “EruDiff: Refactoring Knowledge in Diffusion Models for Advanced Text-to-Image Synthesis” is accepted by ECCV 2026.
  • Jun 2026
    Our paper, titled “G3AFT: Glance Guided Gradient Aligned Fine-Tuning for Visual Autoregressive Models” is accepted by ECCV 2026.
  • May 2026
    Our paper, titled “What Makes Synthetic Data Effective in Image Segmentation” is accepted by ICML 2026.
  • Feb 2026
    Our paper, titled “CTCal: Rethinking Text-to-Image Diffusion Models via Cross-Timestep Self-Calibration” is accepted by CVPR 2026.

Preprints

  1. arXiv'24

    I4VGen: Image as Free Stepping Stone for Text-to-Video Generation.

    Xiefan Guo, Jinlin Liu, Miaomiao Cui, Liefeng Bo, and Di Huang.

Selected Publications Full list on Google Scholar.

  1. ECCV'26

    EruDiff: Refactoring Knowledge in Diffusion Models for Advanced Text-to-Image Synthesis.

    Xiefan Guo, Xinzhu Ma, Haoxiang Ma, Zihao Zhou, and Di Huang.
  2. ECCV'26

    G3AFT: Glance Guided Gradient Aligned Fine-Tuning for Visual Autoregressive Models.

    Jiayi Zhang, Xiefan Guo, Xinzhu Ma, and Di Huang.
  3. ICML'26

    What Makes Synthetic Data Effective in Image Segmentation.

    Jinjin Zhang, Xiefan Guo, Yizhou Jin, Nan Zhou, and Di Huang.
  4. CVPR'26

    CTCal: Rethinking Text-to-Image Diffusion Models via Cross-Timestep Self-Calibration.

    Xiefan Guo, Xinzhu Ma, Haiyu Zhang, and Di Huang.
  5. ICCV'25

    ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning.

    Xiefan Guo, Miaomiao Cui, Liefeng Bo, and Di Huang.
  6. CVPR'25

    Diffusion-4K: Ultra-High-Resolution Image Synthesis with Latent Diffusion Models.

    Jinjin Zhang, Qiuyu Huang, Junjie Liu, Xiefan Guo, and Di Huang.
  7. CVPR'24

    InitNO: Boosting Text-to-Image Diffusion Models via Initial Noise Optimization.

    Xiefan Guo, Jinlin Liu, Miaomiao Cui, Jiankai Li, Hongyu Yang, and Di Huang.
  8. CVPR'24

    Leveraging Predicate and Triplet Learning for Scene Graph Generation.

    Jiankai Li, Yunhong Wang, Xiefan Guo, Ruijie Yang, Weixin Li.
  9. CVPR'22

    ABPN: Adaptive Blend Pyramid Network for Real-Time Local Retouching of Ultra High-Resolution Photo.

    Biwen Lei, Xiefan Guo, Hongyu Yang, Miaomiao Cui, Xuansong Xie, and Di Huang.
  10. ICCV'21

    Image Inpainting via Conditional Texture and Structure Dual Generation.

    Xiefan Guo, Hongyu Yang, and Di Huang.

Honors & Awards

  • Sep 2023
    Outstanding Freshman Scholarship for Ph.D. Student, Beihang University.
  • Oct 2022
    Tansuo Award, Beihang University.
  • Oct 2021
    National Scholarship, Beihang University.
  • Oct 2019
    National Scholarship, Tianjin University.
  • Oct 2018
    Silver Medal, ACM International Collegiate Programming Contest (ACM-ICPC), Asia Regional Contest
  • Oct 2018
    Silver Medal, China Collegiate Programming Contest (CCPC), Regional Contest.

Professional Activities

Conference ReviewerCVPR, ICCV, ECCV, ICML, NeurIPS, ICLR, SIGGRAPH, SIGGRAPH Asia, AAAI, AISTATS, ACM MM, ICMR, ECAI, BMVC, PRCV.

Journal ReviewerTPAMI, IJCV, TVCG, TMM, TCSVT, CVIU, FCS, J-STSP.