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

2021-07-27 06:36:06
Songyang Zhang, Lin Song, Songtao Liu, Zheng Ge, Zeming Li, Xuming He, Jian Sun
arXiv_AI
         
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 this https URL

Abstract (translated)

URL

https://arxiv.org/abs/2108.04230

PDF

https://arxiv.org/pdf/2108.04230.pdf

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