Scholar

Feng Li

Google Scholar ID: mYfWM6oAAAAJ

Hefei University of Technology

Video and Image ProcessingLow-level Computer-vision

Citations & Impact

All-time

Citations

814

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i10-index

Publications

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Contact

Publications

6 items

2026

Cited

2026

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2026

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2026

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2026

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2026

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Resume

Academic Achievements

Publications:
- IEEE TIP, 2025: Prompt to Restore, Restore to Prompt: Cyclic Prompting for Universal Adverse Weather Removal
- IEEE TIP, 2025: Reference-based Iterative Interaction with P^2-Matching for Stereo Image Super-Resolution
- CVPR, 2025: EvEnhancer: Empowering Effectiveness, Efficiency and Generalizability for Continuous Space-Time Video Super-Resolution with Events
- ICLR, 2025: Once-for-All: Controllable Generative Image Compression with Dynamic Granularity Adaption
- IJCV, 2025: SRConvNet: A Transformer-Style ConvNet for Lightweight Image Super-Resolution
- AAAI, 2025: Thinking in Granularity: Dynamic Quantization for Image Super-Resolution by Intriguing Multi-Granularity Clues
- AAAI, 2025: Attend and Enrich: Enhanced Visual Prompt for Zero-Shot Learning
- AAAI, 2025: Sign-IDD: Iconicity Disentangled Diffusion for Sign Language Production
- TPAMI, 2024: PSVMA+: Exploring Multi-granularity Semantic-visual Adaption for Generalized Zero-shot Learning
- Other papers: TII, TOMM, TMM, TCSVT, CVPR 2023 (selected as a highlight paper)
Awards:
- 2nd place on NTIRE 2024 Stereo Image Super-Resolution Challenge-Track 1 (CVPR2024)

Research Experience

Associate Professor with the School of Computer Science and Information Engineering (School of Artificial Intelligence), Hefei University of Technology, under Prof. Meng Wang.

Education

Ph.D. degree: Institute of Information Science, Beijing Jiaotong University (BJTU), China, 2022, supervised by Prof. Huihui Bai; Joint Ph.D. Student: School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore, from Jul. 2021 to Jul. 2022, supervised by Prof. Weisi Lin; Ph.D. completed in Mepro led by Yao Zhao.

Background

Research Interests: Low-level computer vision including AIGC & Detection, text-to-image/video, image/video restoration, compression, and multi-modal models.

Miscellany