2 citations · 3 across the 5 of their papers we have counts for
5 papers
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…
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…
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective
Kai Guo, Hongzhi Wen, Wei Jin +3
Graph neural networks (GNNs) have exhibited remarkable performance under the assumption that test data comes from the same distribution of training data. However, in real-world sce…
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…
From Sky to the Ground: A Large-scale Benchmark and Simple Baseline Towards Real Rain Removal
Yun Guo, Xueyao Xiao, Yi Chang +2
Learning-based image deraining methods have made great progress. However, the lack of large-scale high-quality paired training samples is the main bottleneck to hamper the real ima…