Effective Multi-Object Tracking via Global Object Models and Object Constraint Learning
Sensors, 2022 Effective multi-object tracking is still challenging due to the trade-off between tracking accuracy and speed. Because the recent multi-object tracking (MOT) methods leverage object appearance and motion models so as to associate detections between ...
Yong-Sang Yoo +2 more
doaj +1 more source
Semantic Enhanced Distantly Supervised Relation Extraction via Graph Attention Network
Information, 2020 Distantly Supervised relation extraction methods can automatically extract the relation between entity pairs, which are essential for the construction of a knowledge graph.
Xiaoye Ouyang, Shudong Chen, Rong Wang
doaj +1 more source
IEEE Access, 2021 Object tracking is an important basis for the autonomous navigation of unmanned surface vehicles. However, several problems still must be addressed for a wide applicating of object tracking in unmanned surface vehicles.
Qingze Yu, Bo Wang, Yumin Su
doaj +1 more source
HOTA: A Higher Order Metric for Evaluating Multi-object Tracking [PDF]
International Journal of Computer Vision, 2020 Multi-object tracking (MOT) has been notoriously difficult to evaluate. Previous metrics overemphasize the importance of either detection or association.
Jonathon Luiten +6 more
semanticscholar +1 more source
Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark [PDF]
Computer Vision and Pattern Recognition, 2021 Tracking by natural language specification is a new rising research topic that aims at locating the target object in the video sequence based on its language description.
Xiao Wang +6 more
semanticscholar +1 more source
LaSOT: A High-Quality Benchmark for Large-Scale Single Object Tracking [PDF]
Computer Vision and Pattern Recognition, 2018 In this paper, we present LaSOT, a high-quality benchmark for Large-scale Single Object Tracking. LaSOT consists of 1,400 sequences with more than 3.5M frames in total. Each frame in these sequences is carefully and manually annotated with a bounding box,
Heng Fan +9 more
semanticscholar +1 more source
MOTRv2: Bootstrapping End-to-End Multi-Object Tracking by Pretrained Object Detectors [PDF]
Computer Vision and Pattern Recognition, 2022 In this paper, we propose MOTRv2, a simple yet effective pipeline to bootstrap end-to-end multi-object tracking with a pretrained object detector. Existing end-to-end methods, e.g.
Yuang Zhang, Tiancai Wang, Xiangyu Zhang
semanticscholar +1 more source
Tracking of a Fixed-Shape Moving Object Based on the Gradient Descent Method
Sensors, 2022 Tracking moving objects is one of the most promising yet the most challenging research areas pertaining to computer vision, pattern recognition and image processing.
Haris Masood +6 more
doaj +1 more source
VisEvent: Reliable Object Tracking via Collaboration of Frame and Event Flows [PDF]
IEEE Transactions on Cybernetics, 2021 Different from visible cameras which record intensity images frame by frame, the biologically inspired event camera produces a stream of asynchronous and sparse events with much lower latency.
Xiao Wang +8 more
semanticscholar +1 more source
Object-Tracking Algorithm Combining Motion Direction and Time Series
Applied Sciences, 2023 Object tracking using deep learning is a crucial research direction within intelligent vision processing. One of the key challenges in object tracking is accurately predicting the object’s motion direction in consecutive frames while accounting for the ...
Jianjun Su, Chenmou Wu, Shuqun Yang
doaj +1 more source