3 papers
cs.CV2026
Adapting Depth Anything to Adverse Imaging Conditions with Events
Shihan Peng, Yuyang Xiong, Hanyu Zhou +5
Robust depth estimation under dynamic and adverse lighting conditions is essential for robotic systems. Currently, depth foundation models, such as Depth Anything, achieve great su…
cs.CV2024
Adverse Weather Optical Flow: Cumulative Homogeneous-Heterogeneous Adaptation
Hanyu Zhou, Yi Chang, Zhiwei Shi +4
Optical flow has made great progress in clean scenes, while suffers degradation under adverse weather due to the violation of the brightness constancy and gradient continuity assum…
cs.CV2024
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…