Zehao Chen

Research Fellow

The State Key Laboratory of Brain-Machine Intelligence,
Zhejiang University, Hangzhou, China.

I am currently a research fellow at the State Key Laboratory of Brain-Machine Intelligence, Zhejiang University, and work closely with Prof. Gang Pan, Prof. Huajin Tang, and Prof. Qian Zheng. I received my Ph.D. and M.S. degrees from Zhejiang University (supervisor: Prof. Gang Pan and Prof. Qian Zheng) and Carnegie Mellon University. In 2025, I was selected for the Postdoctoral Innovation Talent Support Program. My research focuses on neuromorphic computing, with a particular interest in developing brain-inspired computational paradigms that enable machines to perceive and understand their surrounding environment with the efficiency of biological systems.

📚 Selected Works (since 2024)

配图 images/CVPR26-dai.png	Dynamic-Static Decomposition for Novel View Synthesis of Dynamic Scenes with Spiking Neurons Lingyun Dai#, Zehao Chen#, Yan Liu, Shi Gu, Peng Lin, De Ma, Huajin Tang, Qian Zheng, Gang Pan The IEEE/CVF Conference on Computer Vision and Pattern Recognition* (CVPR), Jun 2026 [Project] A discontinuous dynamic–static tagging field based on spiking neurons (SNs), reducing uncertainty-induced misclassification near object boundaries.
配图 images/CVPR26-yan.png	eRetinexGS: Retinex Modeling for Low-Light Scene Enhancement via Event Streams and 3D Gaussian Splatting Haojie Yan, Zehao Chen, Yan Liu, Shi Gu, Peng Lin, De Ma, Huajin Tang, Qian Zheng, Gang Pan The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2026 [Project] Two cues of event-guided low-light enhancement; a framework combining Retinex decomposition with 3D Gaussian Splatting.
配图 images/ICCV25.png	E-NeMF: Event-based Neural Motion Field for Novel Space-time View Synthesis of Dynamic Scenes Yan Liu, Zehao Chen, Haojie Yan, De Ma, Huajin Tang, Qian Zheng, Gang Pan International Conference on Computer Vision (ICCV), Oct 2025 [Paper] [Project] Event-guided dynamic scene reconstruction from a monocular event–frame video; accurate complex motion with robustness to event noise and sparsity.
配图 images/AAAI25-chen2.png	Event-guided HDR Video Reconstruction with 3D Gaussian Splatting Zehao Chen, Zhan Lu, De Ma, Huajin Tang, Xudong Jiang, Qian Zheng, Gang Pan Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), Feb 2025 [Project] A scene-based approach to HDR video reconstruction that addresses cross-frame brightness inconsistency.
配图 images/AAAI25-chen1.png	EvHDR-NeRF: Building High Dynamic Range Radiance Fields with Single Exposure Images and Events Zehao Chen, Zhanfeng Liao, De Ma, Huajin Tang, Qian Zheng, Gang Pan Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), Feb 2025 [Paper] [Project] Event-guided HDR radiance field reconstruction from a monocular, single-exposure event–frame video; faithful camera response function (CRF) recovery.
配图 images/AAAI25-yan.png	EvSTVSR: Event Guided Space-Time Video Super-Resolution Haojie Yan, Zhan Lu, Zehao Chen, De Ma, Huajin Tang, Qian Zheng, Gang Pan Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), Feb 2025 [Paper] [Project] Fewer is Better: fewer adjacent frames (with event streams) yield better space–time video super-resolution.
配图 images/IJCAI25-lu.png	EDyGS: Event Enhanced Dynamic 3D Radiance Fields from Blurry Monocular Video Mengxu Lu#, Zehao Chen#, Yan Liu, De Ma, Huajin Tang, Qian Zheng, Gang Pan International Joint Conference on Artificial Intelligence (IJCAI), Aug 2025 [Paper] Exploits multi-view relationships in event streams to disentangle camera motion and object motion.
配图 images/MM24.png	Event-ID: Intrinsic Decomposition Using an Event Camera Zehao Chen#, Zhan Lu#, De Ma, Huajin Tang, Qian Zheng, Gang Pan ACM International Conference on Multimedia (ACM MM), Oct 2024 [Paper] [Project] Event-guided intrinsic decomposition from an event–frame video: geometry, materials, lighting recovery, and relighting. Specular (highlight) cues are obtained from multi-view relationships in event streams.