Master in Computer Science
Student, Beijing Institute of Technology
Curriculum Vitae | Blog


I am a graduated student at Beijing Institute of Technology, advised by Prof. Ying Fu. Before that, I received my B.S. in Computer Science and Technology from Beijing Institute of Technology in 2020.

My research interest lies in the optimization and computer vision. Previously, I primarily worked on diffusion models, proximal algorithm modeling, and image restoration. I also gained experience in some high-level vision tasks during the internship at OpenGVLab, advised by Wenhai Wang.


News

For Fun

  • May 2024: 🌻 Released MuLan - Make your diffusion model multilingual without training.
  • Apr 2024: 🤗 Released OpenDMD - Open sourced one step diffusion model.
  • Oct 2023: 🎉 Checkout our investigation of DALLE3 at Mini-DALLE3.
  • May 2023: 🔥 Released Anything2Image and replication of DragGAN.

Research

  • July 2024: ControlLLM is accepted by ECCV 2024.
  • Nov 2023: HSI-RefSR is accepted by TNNLS.
  • Jul 2023: HSDT is accepted by ICCV 2023.
  • May 2023: Delta-Prox is accepted by SIGGRAPH TOG 2023.
  • Jan 2022: DPHSIR is accepted by Neurocomputing.

Selected Publications
  1. Denoising Diffusion Semantic Segmentation with Mask Prior Modeling
    Preprint, arXiv preprint arXiv:2306.01721. [Code]
    Zeqiang Lai*Yuchen Duan*Jifeng Dai, Ziheng Li, Ying FuHongsheng LiYu Qiao, and Wenhai Wang
  2. Hybrid Spectral Denoising Transformer with Guided Attention
    ICCV 2023, International Conference on Computer Vision. [Poster] [Code]
    Zeqiang Lai, Chenggang Yan, and Ying Fu

Experiences

Services

Journal reviewer: TIP / TGRS

Conference reviewer: CVPR 2022 / ICCV 2021 / PBDL 2021 / ACMMM 2021


Awards
  • National Scholarship China (2022)
  • Academic Scholarship of Beijing Institute of Technology (2020,2022)
  • Honorable Mention, Interdisciplinary Contest in Modeling (2019)
  • First Prize of China Undergraduate Mathematical Contest in Modeling, Beijing (2018)
  • Scholarship for Outstanding Students (2017,2018)