北京邮电大学
博士
曹朴
Pu Cao (曹朴)
Email caopu@bupt.edu.cn
我于 2022 年在北京科技大学获得学士学位，目前自 2022 年起在北京邮电大学智能工程与自动化学院攻读博士学位（预计 2027 年夏天毕业）。
我的研究兴趣包括多模态理解与生成，尤其关注多模态大语言模型与扩散模型。
I received my bachelor’s degree from the University of Science and Technology Beijing (USTB), Beijing, China, in 2022, and I am currently a Ph.D. candidate at the School of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications (BUPT), since 2022 (expected to graduate in summer 2027).
My research interests include multimodal understanding and generation, especially focusing on multimodal large language models and diffusion models.
经历
Experiences
北京科技大学
本科
Beijing University of Posts and Telecommunications
Ph.D.
University of Science and Technology Beijing
B.S.
新闻 News
论文 Publications
Controllable Generation with Text-to-Image Diffusion Models: A Survey
ResDiT: Evoking the Intrinsic Resolution Scalability in Diffusion Transformers
Exploring Position Encoding in Diffusion U-Net for Training-free High-resolution Image Generation
Initialize to Generalize: A Stronger Initialization Pipeline for Sparse-View 3DGS
OMEGAS: Object Mesh Extraction from Large Scenes Guided by Gaussian Segmentation
Quality Transformer for Human Parsing
Preliminary Explorations with GPT-4o(mni) Native Image Generation
Image is All You Need to Empower Large-scale Diffusion Models for In-Domain Generation
E4C: Enhance Editability for Text-Based Image Editing by Harnessing Efficient CLIP Guidance
Frequency-Based Matcher for Long-Tailed Semantic Segmentation
What Decreases Editing Capability? Domain-Specific Hybrid Refinement for Improved GAN Inversion
Controllable Generation with Text-to-Image Diffusion Models: A Survey
ResDiT: Evoking the Intrinsic Resolution Scalability in Diffusion Transformers
Exploring Position Encoding in Diffusion U-Net for Training-free High-resolution Image Generation
Initialize to Generalize: A Stronger Initialization Pipeline for Sparse-View 3DGS
OMEGAS: Object Mesh Extraction from Large Scenes Guided by Gaussian Segmentation
Quality Transformer for Human Parsing
Preliminary Explorations with GPT-4o(mni) Native Image Generation
Image is All You Need to Empower Large-scale Diffusion Models for In-Domain Generation
E4C: Enhance Editability for Text-Based Image Editing by Harnessing Efficient CLIP Guidance
Frequency-Based Matcher for Long-Tailed Semantic Segmentation
What Decreases Editing Capability? Domain-Specific Hybrid Refinement for Improved GAN Inversion
项目 Projects
服务 Service
会议
- ICLR 2026
- CVPR 2025–2026
- ICCV 2025
- ECCV 2024 杰出审稿人奖
- WACV 2024–2026
期刊
- TPAMI
- TIP
- TCSVT
- TMM
- TNNLS
Conferences
- ICLR 2026
- CVPR 2025–2026
- ICCV 2025
- ECCV 2024 Outstanding Reviewer Award
- WACV 2024–2026
Journals
- TPAMI
- TIP
- TCSVT
- TMM
- TNNLS
联系 Contact
快速给我发邮件
caopu@bupt.edu.cnSend me a quick email
caopu@bupt.edu.cn