YOLOv1 to YOLOv10: The fastest and most accurate real-time object detection systems
원문 초록
This is a comprehensive review of the YOLO series of systems. Different from previous literature surveys, this review article re-examines the characteristics of the YOLO series from the latest technical point of view. At the same time, we also analyzed how the YOLO series continued to influence and promote real-time computer vision-related research and led to the subsequent development of computer vision and language models.We take a closer look at how the methods proposed by the YOLO series in the past ten years have affected the development of subsequent technologies and show the applications of YOLO in various fields. We hope this article can play a good guiding role in subsequent real-time computer vision development.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
YOLOv13: Real-Time Object Detection with Hypergraph-Enhanced Adaptive Visual Perception
Detection of Rail Line Track and Human Beings Near the Track to Avoid Accidents
How Real is CARLAs Dynamic Vision Sensor? A Study on the Sim-to-Real Gap in Traffic Object Detection
WD-DETR: Wavelet Denoising-Enhanced Real-Time Object Detection Transformer for Robot Perception with Event Cameras
MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection
WTEFNet: Real-Time Low-Light Object Detection for Advanced Driver-Assistance Systems
토론
이 논문과 연결된 포럼 글이 아직 없습니다.