YOLO系列模型发展史-阿里云开发者社区

YOLO系列模型发展史

2024-10-16 5

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简介： YOLO系列模型从YOLOv3到YOLOv10，不断优化实时目标检测性能和速度。最新版本YOLOv8增加了实例分割、姿态估计等功能。此外，还包括Segment Anything Model（SAM）、MobileSAM、FastSAM、YOLO-NAS、RT-DETR和YOLO-World等模型，分别在不同场景下提供高效的目标检测和分割能力。

YOLOv3: The third iteration of the YOLO model family, originally by Joseph Redmon, known for its efficient real-time object detection capabilities.
YOLOv4: A darknet-native update to YOLOv3, released by Alexey Bochkovskiy in 2020.
YOLOv5: An improved version of the YOLO architecture by Ultralytics, offering better performance and speed trade-offs compared to previous versions.
YOLOv6: Released by Meituan in 2022, and in use in many of the company's autonomous delivery robots.
YOLOv7: Updated YOLO models released in 2022 by the authors of YOLOv4.
YOLOv8 NEW 🚀: The latest version of the YOLO family, featuring enhanced capabilities such as instance segmentation, pose/keypoints estimation, and classification.
YOLOv9: An experimental model trained on the Ultralytics YOLOv5 codebase implementing Programmable Gradient Information (PGI).
YOLOv10: By Tsinghua University, featuring NMS-free training and efficiency-accuracy driven architecture, delivering state-of-the-art performance and latency.
Segment Anything Model (SAM): Meta's Segment Anything Model (SAM).
Mobile Segment Anything Model (MobileSAM): MobileSAM for mobile applications, by Kyung Hee University.
Fast Segment Anything Model (FastSAM): FastSAM by Image & Video Analysis Group, Institute of Automation, Chinese Academy of Sciences.
YOLO-NAS: YOLO Neural Architecture Search (NAS) Models.
Realtime Detection Transformers (RT-DETR): Baidu's PaddlePaddle Realtime Detection Transformer (RT-DETR) models.
YOLO-World: Real-time Open Vocabulary Object Detection models from Tencent AI Lab.

YOLO系列模型发展史

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