most citedSeeing Motion at Nighttime with an Event Camera

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV20241 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.CV20241 cited

Seeing Motion at Nighttime with an Event Camera

Haoyue Liu, Shihan Peng, Lin Zhu +3

We focus on a very challenging task: imaging at nighttime dynamic scenes. Most previous methods rely on the low-light enhancement of a conventional RGB camera. However, they would…

cs.CV2024

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…

cs.CV2024

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…

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…

cs.CV2023

Unsupervised Hierarchical Domain Adaptation for Adverse Weather Optical Flow

Hanyu Zhou, Yi Chang, Gang Chen +1

Optical flow estimation has made great progress, but usually suffers from degradation under adverse weather. Although semi/full-supervised methods have made good attempts, the doma…