1 citations · 2 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
JSTR: Joint Spatio-Temporal Reasoning for Event-based Moving Object Detection
Hanyu Zhou, Zhiwei Shi, Hao Dong +3
Event-based moving object detection is a challenging task, where static background and moving object are mixed together. Typically, existing methods mainly align the background eve…
Bring Event into RGB and LiDAR: Hierarchical Visual-Motion Fusion for Scene Flow
Hanyu Zhou, Yi Chang, Zhiwei Shi +1
Single RGB or LiDAR is the mainstream sensor for the challenging scene flow, which relies heavily on visual features to match motion features. Compared with single modality, existi…
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…