YOLO (You Only Look Once)
YOLO (You Only Look Once) is a family of single-stage, real-time object-detection models that predict bounding boxes and class probabilities in one forward pass of the network — trading a little accuracy for speed.
From the original 2016 paper to today's Ultralytics releases (YOLOv8, YOLO11) and open-vocabulary variants like YOLO-World, the YOLO family is the most widely used real-time object detector in computer vision. Here is our latest reporting and guides across YOLO versions, benchmarks, and how to choose one.
Latest coverage
Articles
NewsWeekly AI Highlights Review: October 1–7
NewsYOLOv11, the latest in the Ultralytics YOLO series, is remarkably flexible and versatile
DigestData Phoenix Digest - ISSUE 4.2024
PapersYOLO-World: Real-Time Open-Vocabulary Object Detection
Voxel51Why 2023 was the most exciting year in computer vision history (so far)
DigestData Phoenix Digest - ISSUE 4.2023
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A Guide to the YOLO Family of Computer Vision Models
DigestData Phoenix Digest - ISSUE 2.2023
DigestData Phoenix Digest - ISSUE 61
DigestData Phoenix Digest - ISSUE 55
DigestData Phoenix Digest - ISSUE 54
DigestData Phoenix Digest - ISSUE 53