Res2Net
Introduction
@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.