YOLOv8-QSD: An Improved Small Object Detection Algorithm for Autonomous Vehicles Based on YOLOv8

As self-driving vehicles become more prevalent, the speed and accuracy of detecting surrounding objects through onboard sensing technology have become increasingly important. The YOLOv8-QSD network is a novel anchor-free driving scene detection network that builds on YOLOv8 and ensures detection accuracy while maintaining efficiency. The network’s backbone employs structural reparameterization techniques to transform the Diverse Branch Block based model. To accurately detect small objects, it integrates features of different scales and implements a bifpn-based feature pyramid after the backbone. To address the challenge of long-range detection in driving scenarios, a query-based model with a new pipeline…

• NN
  National Natural Science Foundation of China

  Awards: U20A20333, 52072160, 52225212