PofoliaShared via Pofolia

· 2023

YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors

Chien-Yao Wang, Alexey Bochkovskiy, Hong-Yuan Mark Liao

Short summary

YOLOv7 achieves state-of-the-art real-time object detection by combining a trainable bag-of-freebies, architectural improvements, and compound scaling, outperforming all known detectors in speed and accuracy.

AI-generated from the title and abstract; the full text is not read.

TakeawaysIn the app
Key pointsIn the app
Ask the paperIn the app

The rest is in the Pofolia app

Takeaways, key points and questions to the paper; new summaries every day for your field. Free.

Sign in on the web to open

Field: Computer Vision and Pattern Recognition

Computer Vision and Pattern RecognitionComputer Science