About
I am pursuing a Ph.D. in robotic perception with the Robotics and Perception Group, led by Prof. Davide Scaramuzza. I am also an associated doctoral researcher with the ETH AI Center.
My research interests sit at the intersection of vision, learning, and robotics, with a focus on event-based visual sensing and transferable representation learning for robotic tasks such as motion estimation, scene understanding, and robust perception in challenging conditions.
Before starting my Ph.D., I completed my Master's degree with distinction in Robotics, Systems, and Control at ETH Zurich. I also worked at the Computer Vision and Geometry Group on object retrieval under motion blur, and at Huawei Switzerland on image quality enhancement.
Prior to my Master's, I received my Bachelor's degree with distinction in Engineering from Huazhong University of Science and Technology.
Selected Publications
View All ->Event-Aided Sharp Radiance Field Reconstruction for Fast-Flying Drones
Rong Zou*, Marco Cannici*, Davide Scaramuzza
IEEE Transactions on Robotics (TRO)
A unified event-and-frame framework for sharp radiance field reconstruction from fast drone flights affected by motion blur and noisy pose estimates.
Retrieval Robust to Object Motion Blur
Rong Zou, Marc Pollefeys, Denys Rozumnyi
European Conference on Computer Vision (ECCV)
A method and dataset for learning robust representations capable of bidirectional matching between motion-blurred objects and their deblurred counterparts.
News
Our paper "Event-Aided Sharp Radiance Field Reconstruction for Fast-Flying Drones" appeared in IEEE Transactions on Robotics.
Our paper "Low-latency Event-based Object Detection with Spatially-Sparse Linear Attention" is available on arXiv.
Our paper "FastEventDGS: Deformable Gaussian Splatting for Fast Dynamic Scenes from a Single Event Camera" was accepted by CVPR 2026.