7 citations · 24 across the 9 of their papers we have counts for
9 papers
CityTrack: Improving City-Scale Multi-Camera Multi-Target Tracking by Location-Aware Tracking and Box-Grained Matching
Jincheng Lu, Xipeng Yang, Jin Ye +4
Multi-Camera Multi-Target Tracking (MCMT) is a computer vision technique that involves tracking multiple targets simultaneously across multiple cameras. MCMT in urban traffic visua…
ByteTrackV2: 2D and 3D Multi-Object Tracking by Associating Every Detection Box
Yifu Zhang, Xinggang Wang, Xiaoqing Ye +6
Multi-object tracking (MOT) aims at estimating bounding boxes and identities of objects across video frames. Detection boxes serve as the basis of both 2D and 3D MOT. The inevitabl…
Ambiguity-Resistant Semi-Supervised Learning for Dense Object Detection
Chang Liu, Weiming Zhang, Xiangru Lin +6
With basic Semi-Supervised Object Detection (SSOD) techniques, one-stage detectors generally obtain limited promotions compared with two-stage clusters. We experimentally find that…
Repainting and Imitating Learning for Lane Detection
Yue He, Minyue Jiang, Xiaoqing Ye +5
Current lane detection methods are struggling with the invisibility lane issue caused by heavy shadows, severe road mark degradation, and serious vehicle occlusion. As a result, di…
Weakly-Supervised Spatio-Temporal Anomaly Detection in Surveillance Video
Jie Wu, Wei Zhang, Guanbin Li +5
In this paper, we introduce a novel task, referred to as Weakly-Supervised Spatio-Temporal Anomaly Detection (WSSTAD) in surveillance video. Specifically, given an untrimmed video,…
Box-Aware Feature Enhancement for Single Object Tracking on Point Clouds
Chaoda Zheng, Xu Yan, Jiantao Gao +4
Current 3D single object tracking approaches track the target based on a feature comparison between the target template and the search area. However, due to the common occlusion in…