activity
20242026
most citedCoSEC: A Coaxial Stereo Event Camera Dataset for Autonomous Driving

1 citations · 1 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2026

High-Quality and Efficient Turbulence Mitigation with Events

Xiaoran Zhang, Jian Ding, Yuxing Duan +4

Turbulence mitigation (TM) is highly ill-posed due to the stochastic nature of atmospheric turbulence. Most methods rely on multiple frames recorded by conventional cameras to capt…

cs.CV2025

STD-GS: Exploring Frame-Event Interaction for SpatioTemporal-Disentangled Gaussian Splatting to Reconstruct High-Dynamic Scene

Hanyu Zhou, Haonan Wang, Haoyue Liu +3

High-dynamic scene reconstruction aims to represent static background with rigid spatial features and dynamic objects with deformed continuous spatiotemporal features. Typically, e…

cs.CV2025

Bridge Frame and Event: Common Spatiotemporal Fusion for High-Dynamic Scene Optical Flow

Hanyu Zhou, Haonan Wang, Haoyue Liu +3

High-dynamic scene optical flow is a challenging task, which suffers spatial blur and temporal discontinuous motion due to large displacement in frame imaging, thus deteriorating t…

cs.CV2024★ 1 cited

CoSEC: A Coaxial Stereo Event Camera Dataset for Autonomous Driving

Shihan Peng, Hanyu Zhou, Hao Dong +5

Conventional frame camera is the mainstream sensor of the autonomous driving scene perception, while it is limited in adverse conditions, such as low light. Event camera with high…

cs.CV2024

LED: A Large-scale Real-world Paired Dataset for Event Camera Denoising

Yuxing Duan, Shihan Peng, Lin Zhu +4

Event camera has significant advantages in capturing dynamic scene information while being prone to noise interference, particularly in challenging conditions like low threshold an…

cs.CV2024

Exploring the Common Appearance-Boundary Adaptation for Nighttime Optical Flow

Hanyu Zhou, Yi Chang, Haoyue Liu +4

We investigate a challenging task of nighttime optical flow, which suffers from weakened texture and amplified noise. These degradations weaken discriminative visual features, thus…