mlsanityData to 14 Oct 2026

Video object tracking based on YOLOv7 and DeepSORT

arXiv 2207.12202 ↗First posted 25 Jul 2022cs.CVcited by 3

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Abstract (arXiv)

Multiple object tracking (MOT) is an important technology in the field of computer vision, which is widely used in automatic driving, intelligent monitoring, behavior recognition and other directions. Among the current popular MOT methods based on deep learning, Detection Based Tracking (DBT) is the most widely used in industry, and the performance of them depend on their object detection network. At present, the DBT algorithm with good performance and the most widely used is YOLOv5-DeepSORT. Inspired by YOLOv5-DeepSORT, with the proposal of YOLOv7 network, which performs better in object detection, we apply YOLOv7 as the object detection part to the DeepSORT, and propose YOLOv7-DeepSORT. After experimental evaluation, compared with the previous YOLOv5-DeepSORT, YOLOv7-DeepSORT performances better in tracking accuracy.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 18 of its 24 references that are in the map. First posted on arXiv 25 Jul 2022.

Builds on

18 of 24 references.

References · 18

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6 more
  1. 2020FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Trackingcited by 490
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Citing papers per year: 2022: 1; 2023: 1; 2024: 0; 2025: 1.

3 papers.