Real-time object detector YOLOv10 beats YOLOv9 in speed and size by consistent assignments
Real-time object detector YOLOv10 beats YOLOv9 in speed and size by consistent assignments
YOLOv10: Real-Time End-to-End Object Detection
arXiv paper abstract https://arxiv.org/abs/2405.14458
arXiv PDF paper https://arxiv.org/pdf/2405.14458
... YOLOs have emerged as the predominant paradigm in ... real-time object detection owing to their effective balance between computational cost and detection performance.
... aim to further advance the performance-efficiency boundary of YOLOs from both the post-processing and model architecture.
... present the consistent dual assignments for NMS-free training of YOLOs, which brings competitive performance and low inference latency simultaneously.
... introduce the holistic efficiency-accuracy driven model design strategy for YOLOs.
... optimize ... components of YOLOs from both efficiency and accuracy perspectives, which greatly reduces the computational overhead and enhances the capability.
... YOLOv10 achieves state-of-the-art ... across ... model scales ... Compared with YOLOv9-C, YOLOv10-B has 46% less latency and 25% fewer parameters for the same performance.
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