Jinxiu (Sherry) Liang
Researcher, National Institute of Informatics, Tokyo, Japan
Research vision
“Information is the resolution of uncertainty.” — after Claude Shannon
A frame mostly re-measures what the previous frame already established; the new information lives in change. I build imaging systems that sample the world on its own clock, measuring its fast, faint dynamics with a fraction of the light and data.
I am a researcher at the National Institute of Informatics (NII), hosted by Prof. Imari Sato, measuring fast physical phenomena in continuous time. Before joining NII, I was a postdoctoral fellow with Prof. Boxin Shi at the National Engineering Research Center of Visual Technology, Peking University, focusing on high-speed, low-light photography with neuromorphic cameras. I received my Ph.D. and B.Eng. from South China University of Technology under Prof. Yong Xu, working closely with Prof. Hui Ji and Prof. Yuhui Quan on optimization and image priors for inverse problems.
Email | Google Scholar | DBLP | ORCID | GitHub | LinkedIn
My research interests include:
- Sensing on the world’s clock: asynchronous detectors (event, spike, and single-photon) as continuous-time instruments, maximizing information per timestamp to reconstruct the field between and beyond frames.
- Time-coded illumination: physical quantities written into time and read back from timestamps: shape, spectrum, and vibration at high speed.
- Physics-guided generative priors: zero-shot reconstruction where paired data cannot exist at scale, from photon-starved scenes to unconventional sensors and imaging beyond photography.
Publications (Selected | Full List)
Author role markers: # equal contribution (co-first author); * (co-)corresponding author; † co-mentored student.
- IEEE International Conference on Computer Vision (ICCV), 2025 (Highlight, top 3% of 11,239 submissions)Lighting written into time, normals read from events: surpassing frame-based accuracy at 5% of the bandwidth.
- IEEE International Conference on Computer Vision (ICCV), 2025Physics-guided diffusion turns sub-millisecond spike streams into color video, zero-shot.
- IEEE International Conference on Computer Vision (ICCV), 2023Fast and dim at once: events keep low-light video sharp and temporally coherent.
- IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025 (Highlight, top 3% of 13,008 submissions)A sweeping rainbow encodes spectra in event timing: hyperspectral video of dynamic scenes.
- IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024 (Best Paper Runner-Up, top 4 of 11,532 submissions)Surface normals in real time, from an event camera watching changing light.
- AAAI Conference on Artificial Intelligence (AAAI), 2025Pre-trained latent diffusion as the prior: low-light enhancement with zero training pairs.
- Advances in Neural Information Processing Systems (NeurIPS), 2024Visual prompting lets image-domain foundation models read event streams, no event training.
- IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024Modeling per-pixel latency makes event timestamps accurate where they drift most: in the dark.
- IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2022Enhancement learned from nothing but the input image, via discrepant untrained priors.
- IEEE Transactions on Multimedia (TMM), 2021Multi-exposure imagined from one dark shot makes faces detectable at night.
Research Grants (as PI)
- 2026 · Physics-Constrained Continuous Temporal Field Reconstruction from Asynchronous Event Streams for High-Speed Scene Analysis, JSPS KAKENHI Grant-in-Aid for Early-Career Scientists [link]
- 2025 · Generative Neuromorphic Photography for Low-Light High-Speed Scenarios, National Institute of Informatics
- 2023 · Key Technologies of Event-Guided Low-Light High-Speed Photography, National Natural Science Foundation of China (Young Scientists Fund)
- 2022 · Uncertainty Modeling for Image Enhancement in Real-World Low-Light Scenarios, China Postdoctoral Science Foundation
Honors & Awards
- Best Paper Runner-Up, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024 [link]
- Second Prize, Science and Technology Progress Award, Guangdong Province, 2020 [link]
Reviewer Awards:
- Outstanding Reviewer (1 of only 4), International Journal of Computer Vision (IJCV), 2023 [link]
- Outstanding Reviewer (top 5%), CVPR 2026 [link]
- Gold Reviewer (top 25%), ICML 2026 [link]
- Top Reviewer (top 8%), NeurIPS 2024 [link]
Professional Service
- Journal reviewer: IEEE TPAMI · IJCV · IEEE TIP · IEEE TMM · IEEE TCI · IEEE TCSVT · IEEE TIM · Information Fusion
- Program committee / conference reviewer: CVPR 2022–2026 · ICCV 2023, 2025 · ECCV 2022, 2024, 2026 · NeurIPS 2024, 2025 · ICML 2025, 2026 · ICLR 2024 · AAAI 2023, 2025
Teaching
- Spring 2022–2025 · Guest Lecturer, Computational Photography, Peking University, Lecture 11 (Intrinsic Image Decomposition)
- Spring 2017–2020 · Teaching Assistant, Visual Computing, South China University of Technology
- Fall 2016–2020 · Teaching Assistant, Cryptography and Security Protocols, South China University of Technology
Leadership & Service
- 2015 · Vice President (1 of 6 elected campus-wide), Student Union, South China University of Technology
- 2015 · Three-Star Volunteer community-service award, South China University of Technology
- 2011 · Outstanding Student Leader (sole awardee campus-wide), Guangdong Province