activity
20172022
most citedWhen, Where, and What? A New Dataset for Anomaly Detection in Driving Videos

38 citations · 119 across the 7 of their papers we have counts for

collaborators

13 papers

cs.CV2022

MeMOT: Multi-Object Tracking with Memory

Jiarui Cai, Mingze Xu, Wei Li +4

We propose an online tracking algorithm that performs the object detection and data association under a common framework, capable of linking objects after a long time span. This is…

cs.CV202133 cited

Semi-TCL: Semi-Supervised Track Contrastive Representation Learning

Wei Li, Yuanjun Xiong, Shuo Yang +3

Online tracking of multiple objects in videos requires strong capacity of modeling and matching object appearances. Previous methods for learning appearance embedding mostly rely o…

cs.CV2020

Learning Self-Consistency for Deepfake Detection

Tianchen Zhao, Xiang Xu, Mingze Xu +3

We propose a new method to detect deepfake images using the cue of the source feature inconsistency within the forged images. It is based on the hypothesis that images' distinct so…

cs.CV2020

Deep Tiered Image Segmentation For Detecting Internal Ice Layers in Radar Imagery

Yuchen Wang, Mingze Xu, John Paden +3

Understanding the structure of Earth's polar ice sheets is important for modeling how global warming will impact polar ice and, in turn, the Earth's climate. Ground-penetrating rad…

cs.CV202038 cited

When, Where, and What? A New Dataset for Anomaly Detection in Driving Videos

Yu Yao, Xizi Wang, Mingze Xu +3

Video anomaly detection (VAD) has been extensively studied. However, research on egocentric traffic videos with dynamic scenes lacks large-scale benchmark datasets as well as effec…

cs.CV201921 cited

Embodied Visual Recognition

Jianwei Yang, Zhile Ren, Mingze Xu +4

Passive visual systems typically fail to recognize objects in the amodal setting where they are heavily occluded. In contrast, humans and other embodied agents have the ability to…