4.7 Article

RelationTrack: Relation-Aware Multiple Object Tracking With Decoupled Representation

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

MAT: Motion-aware multi-object tracking

Shoudong Han et al.

Summary: In this paper, an enhanced MOT paradigm called Motion-Aware Tracker (MAT) is proposed to address the challenges of camera motion, fast motion, and occlusion in modern multi-object tracking systems. MAT focuses on high-performance motion-based prediction, reconnection, and association to ensure the quality of tracking.

NEUROCOMPUTING (2022)

Article Computer Science, Artificial Intelligence

HOTA: A Higher Order Metric for Evaluating Multi-object Tracking

Jonathon Luiten et al.

Summary: The higher order tracking accuracy (HOTA) is a novel evaluation metric for multi-object tracking that balances accurate detection, association, and localization. It decomposes into sub-metrics to evaluate different error types separately, providing clear analysis of tracking performance. The HOTA scores align better with human visual evaluation of tracking performance compared to established metrics.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2021)

Article Computer Science, Artificial Intelligence

FairMOT: On the Fairness of Detection and Re-identification in Multiple Object Tracking

Yifu Zhang et al.

Summary: Multi-object tracking is a crucial problem in computer vision, and formulating it as multi-task learning of object detection and re-ID in a single network can lead to joint optimization of the two tasks. However, competition between the tasks needs to be addressed, and the proposed FairMOT method based on CenterNet architecture achieves high accuracy for both detection and tracking through detailed designs and empirical studies.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2021)

Article Computer Science, Information Systems

Person Re-Identification in Aerial Imagery

Shizhou Zhang et al.

Summary: The paper introduces research on person re-identification in aerial imagery, provides a large-scale aerial person ReID dataset named PRAI-1581, and experimental results show that re-identifying persons in aerial imagery is a challenging problem.

IEEE TRANSACTIONS ON MULTIMEDIA (2021)

Article Computer Science, Artificial Intelligence

Deep learning in video multi-object tracking: A survey

Gioele Ciaparrone et al.

NEUROCOMPUTING (2020)

Article Computer Science, Information Systems

Multiplex Labeling Graph for Near-Online Tracking in Crowded Scenes

Yang Zhang et al.

IEEE INTERNET OF THINGS JOURNAL (2020)

Article Computer Science, Information Systems

A New Method and Benchmark for Detecting Co-Saliency Within a Single Image

Hongkai Yu et al.

IEEE TRANSACTIONS ON MULTIMEDIA (2020)

Article Computer Science, Artificial Intelligence

CamStyle: A Novel Data Augmentation Method for Person Re-Identification

Zhun Zhong et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2019)

Article Computer Science, Information Systems

Multi-Correlation Filters With Triangle-Structure Constraints for Object Tracking

Weijian Ruan et al.

IEEE TRANSACTIONS ON MULTIMEDIA (2019)

Article Engineering, Electrical & Electronic

T-CNN: Tubelets With Convolutional Neural Networks for Object Detection From Videos

Kai Kang et al.

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2018)

Article Computer Science, Information Systems

AENet: Learning Deep Audio Features for Video Analysis

Naoya Takahashi et al.

IEEE TRANSACTIONS ON MULTIMEDIA (2018)

Article Computer Science, Artificial Intelligence

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Shaoqing Ren et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2017)

Proceedings Paper Computer Science, Artificial Intelligence

CityPersons: A Diverse Dataset for Pedestrian Detection

Shanshan Zhang et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Deformable Convolutional Networks

Jifeng Dai et al.

2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Exploit All the Layers: Fast and Accurate CNN Object Detector with Scale Dependent Pooling and Cascaded Rejection Classifiers

Fan Yang et al.

2016 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (2016)

Article Computer Science, Artificial Intelligence

Object Detection with Discriminatively Trained Part-Based Models

Pedro F. Felzenszwalb et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2010)

Article Engineering, Electrical & Electronic

Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics

Keni Bernardin et al.

EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING (2008)