surveillance_monitoring/dependence/PaddleDetection/configs/res2net

Res2Net

Introduction

• Res2Net: A New Multi-scale Backbone Architecture: https://arxiv.org/abs/1904.01169

  @article{DBLP:journals/corr/abs-1904-01169,
  author    = {Shanghua Gao and
             Ming{-}Ming Cheng and
             Kai Zhao and
             Xinyu Zhang and
             Ming{-}Hsuan Yang and
             Philip H. S. Torr},
  title     = {Res2Net: {A} New Multi-scale Backbone Architecture},
  journal   = {CoRR},
  volume    = {abs/1904.01169},
  year      = {2019},
  url       = {http://arxiv.org/abs/1904.01169},
  archivePrefix = {arXiv},
  eprint    = {1904.01169},
  timestamp = {Thu, 25 Apr 2019 10:24:54 +0200},
  biburl    = {https://dblp.org/rec/bib/journals/corr/abs-1904-01169},
  bibsource = {dblp computer science bibliography, https://dblp.org}
  }
  

Model Zoo

Backbone	Type	Image/gpu	Lr schd	Inf time (fps)	Box AP	Mask AP	Download	Configs
Res2Net50-FPN	Faster	2	1x	-	40.6	-	model	config
Res2Net50-FPN	Mask	2	2x	-	42.4	38.1	model	config
Res2Net50-vd-FPN	Mask	2	2x	-	42.6	38.1	model	config

Note: all the above models are trained with 8 gpus.