Workshop on Autonomous Driving at CVPR 2021: Technical Report for Streaming Perception Challenge

• URL: http://arxiv.org/abs/2108.04230v1
• Date: Tue, 27 Jul 2021 06:36:06 GMT
• Title: Workshop on Autonomous Driving at CVPR 2021: Technical Report for Streaming Perception Challenge
• Authors: Songyang Zhang and Lin Song and Songtao Liu and Zheng Ge and Zeming Li and Xuming He and Jian Sun
• Abstract summary: We introduce our real-time 2D object detection system for the realistic autonomous driving scenario. Our detector is built on a newly designed YOLO model, called YOLOX. On the Argoverse-HD dataset, our system achieves 41.0 streaming AP, which surpassed second place by 7.8/6.1 on detection-only track/fully track, respectively.
• Score: 57.647371468876116
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this report, we introduce our real-time 2D object detection system for the realistic autonomous driving scenario. Our detector is built on a newly designed YOLO model, called YOLOX. On the Argoverse-HD dataset, our system achieves 41.0 streaming AP, which surpassed second place by 7.8/6.1 on detection-only track/fully track, respectively. Moreover, equipped with TensorRT, our model achieves the 30FPS inference speed with a high-resolution input size (e.g., 1440-2304). Code and models will be available at https://github.com/Megvii-BaseDetection/YOLOX

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