YOLOv7 Outperforms All Object Detectors, Reduces Costs by 50%
Academia Sinicaâs YOLOv7 Outperforms All Object Detectors, Reduces Costs by 50%
“The 2016 release at CVPR of the YOLO (You Only Look Once) real-time object detector revolutionized the field of computer vision. YOLO delivered unprecedented speed and accuracy on a fundamental task with applications in autonomous driving, robotics, security, medical image analysis and more. Various techniques and tricks (multi-scale predictions, a better backbone classifier, etc.) have since been implemented to improve YOLO training and boost performance.
A research team from Taiwan’s Institute of Information Science, Academia Sinica furthers YOLO development in their new paper YOLOv7: Trainable Bag-Of-Freebies Sets New State-Of-The-Art for Real-Time Object Detectors. This latest YOLO version introduces novel “extend” and “compound scaling” methods that effectively utilize parameters and computation; and surpasses all known real-time object detectors in speed and accuracy…”