OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 11.03.2026, 13:11

Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.

YOLOv3: An Incremental Improvement

2018·5.881 Zitationen·arXiv (Cornell University)Open Access
Volltext beim Verlag öffnen

5.881

Zitationen

2

Autoren

2018

Jahr

Abstract

We present some updates to YOLO! We made a bunch of little design changes to make it better. We also trained this new network that's pretty swell. It's a little bigger than last time but more accurate. It's still fast though, don't worry. At 320x320 YOLOv3 runs in 22 ms at 28.2 mAP, as accurate as SSD but three times faster. When we look at the old .5 IOU mAP detection metric YOLOv3 is quite good. It achieves 57.9 mAP@50 in 51 ms on a Titan X, compared to 57.5 mAP@50 in 198 ms by RetinaNet, similar performance but 3.8x faster. As always, all the code is online at https://pjreddie.com/yolo/

Ähnliche Arbeiten

Autoren

Themen

Advanced Image and Video Retrieval TechniquesAdvanced Neural Network ApplicationsRetinal Imaging and Analysis
Volltext beim Verlag öffnen