A comprehensive review of YOLO: From YOLOv1 to YOLOv8 and beyond
J Terven, D Cordova-Esparza - arXiv preprint arXiv:2304.00501, 2023 - arxiv.org
YOLO has become a central real-time object detection system for robotics, driverless cars,
and video monitoring applications. We present a comprehensive analysis of YOLO's …
and video monitoring applications. We present a comprehensive analysis of YOLO's …
NTIRE 2023 challenge on efficient super-resolution: Methods and results
This paper reviews the NTIRE 2023 challenge on efficient single-image super-resolution
with a focus on the proposed solutions and results. The aim of this challenge is to devise a …
with a focus on the proposed solutions and results. The aim of this challenge is to devise a …
YOLOv6: A single-stage object detection framework for industrial applications
For years, the YOLO series has been the de facto industry-level standard for efficient object
detection. The YOLO community has prospered overwhelmingly to enrich its use in a …
detection. The YOLO community has prospered overwhelmingly to enrich its use in a …
Detrs beat yolos on real-time object detection
Y Zhao, W Lv, S Xu, J Wei, G Wang… - Proceedings of the …, 2024 - openaccess.thecvf.com
The YOLO series has become the most popular framework for real-time object detection due
to its reasonable trade-off between speed and accuracy. However we observe that the …
to its reasonable trade-off between speed and accuracy. However we observe that the …
Bytetrack: Multi-object tracking by associating every detection box
Multi-object tracking (MOT) aims at estimating bounding boxes and identities of objects in
videos. Most methods obtain identities by associating detection boxes whose scores are …
videos. Most methods obtain identities by associating detection boxes whose scores are …
Rtmdet: An empirical study of designing real-time object detectors
In this paper, we aim to design an efficient real-time object detector that exceeds the YOLO
series and is easily extensible for many object recognition tasks such as instance …
series and is easily extensible for many object recognition tasks such as instance …
Wise-IoU: bounding box regression loss with dynamic focusing mechanism
Z Tong, Y Chen, Z Xu, R Yu - arXiv preprint arXiv:2301.10051, 2023 - arxiv.org
The loss function for bounding box regression (BBR) is essential to object detection. Its good
definition will bring significant performance improvement to the model. Most existing works …
definition will bring significant performance improvement to the model. Most existing works …
Real-time multi-class helmet violation detection using few-shot data sampling technique and yolov8
Traffic safety is a major global concern. Helmet usage is a key factor in preventing head
injuries and fatalities caused by motorcycle accidents. However, helmet usage violations …
injuries and fatalities caused by motorcycle accidents. However, helmet usage violations …
The 8th AI City Challenge
Abstract The eighth AI City Challenge highlighted the convergence of computer vision and
artificial intelligence in areas like retail warehouse settings and Intelligent Traffic Systems …
artificial intelligence in areas like retail warehouse settings and Intelligent Traffic Systems …
DenseSPH-YOLOv5: An automated damage detection model based on DenseNet and Swin-Transformer prediction head-enabled YOLOv5 with attention mechanism
Objective. Computer vision-based up-to-date accurate damage classification and
localization are of decisive importance for infrastructure monitoring, safety, and the …
localization are of decisive importance for infrastructure monitoring, safety, and the …