Academia Sinica’s YOLOv7 Outperforms All Object Detectors, Reduces Costs by 50%

In the new paper YOLOv7: Trainable Bag-Of-Freebies Sets New State-Of-The-Art for Real-Time Object Detectors, an Academia Sinica research team releases YOLOv7. 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.

academia ai artificial intelligence computer vision & graphics costs deep-neural-networks machine learning machine learning & data science ml object-detection popular research technology yolo yolov7