Fetching the paper…
Reading the bibliography…
In this report, we introduce our real-time 2D object detection system for the realistic autonomous driving scenario.
Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
Earlier work this paper cites.
The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
Earlier work this paper cites.
Pytorch: An imperative style, high-performance deep learning library
Paszke et al · 2019
Earlier work this paper cites.
Yolov4: Optimal speed and accuracy of object detection
Alexey Bochkovskiy, Chien-Yao Wang, and Hong-Yuan Mark Liao · 2020
Cited alongside, same era.
nuscenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2020
Cited alongside, same era.
Towards streaming perception
Mengtian Li, Yu-Xiong Wang, and Deva Ramanan · 2020
Cited alongside, same era.
https://github.com/nvidia-ai-iot/torch2trt
NVIDIA
Cited in the paper.
https://github.com/ultralytics/yolov5
ultralytics
Cited in the paper.
Bdd100k: A diverse driving dataset for heterogeneous multitask learning
Fisher Yu, Haofeng Chen, Xin Wang, Wenqi Xian, Yingying Chen, Fangchen Liu, Vashisht Madhavan, and Trevor Darrell · 2020
Later among the works it cites.
Ota: Optimal transport assignment for object detection
Zheng Ge, Songtao Liu, Zeming Li, Osamu Yoshie, and Jian Sun · 2021
Closest in time.
Yolox: Exceeding yolo series in 2021
Zheng Ge, Songtao Liu, Feng Wang, Zeming Li, and Jian Sun · 2021
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…