You Only Look Once

You Only Look Once
Original author(s)	Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi
Initial release	2015
Stable release	YOLOv12 / 2025-02-20
Written in	Python
Type	Object detection; Convolutional neural network; Computer vision;
Website	pjreddie.com/darknet/yolo/

Objects detected with OpenCV's Deep Neural Network module by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes

You Only Look Once (YOLO) is a series of real-time object detection systems based on convolutional neural networks. First introduced by Joseph Redmon et al. in 2015,^[1] YOLO has undergone several iterations and improvements, becoming one of the most popular object detection frameworks.^[2]

The name "You Only Look Once" refers to the fact that the algorithm requires only one forward propagation pass through the neural network to make predictions, unlike previous region proposal-based techniques like R-CNN that require thousands for a single image.

^ Redmon, Joseph; Divvala, Santosh; Girshick, Ross; Farhadi, Ali (2016-05-09). "You Only Look Once: Unified, Real-Time Object Detection". arXiv:1506.02640 [cs.CV].
^ Terven, Juan; Córdova-Esparza, Diana-Margarita; Romero-González, Julio-Alejandro (2023-11-20). "A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS". Machine Learning and Knowledge Extraction. 5 (4): 1680–1716. arXiv:2304.00501. doi:10.3390/make5040083. ISSN 2504-4990.

[:2-1] Redmon, Joseph; Divvala, Santosh; Girshick, Ross; Farhadi, Ali (2016-05-09). "You Only Look Once: Unified, Real-Time Object Detection". arXiv:1506.02640 [cs.CV].

[:0-2] Terven, Juan; Córdova-Esparza, Diana-Margarita; Romero-González, Julio-Alejandro (2023-11-20). "A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS". Machine Learning and Knowledge Extraction. 5 (4): 1680–1716. arXiv:2304.00501. doi:10.3390/make5040083. ISSN 2504-4990.

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