ccnet

CCNet: Criss-Cross Attention for Semantic Segmentation

Introduction

[ALGORITHM]

@article{huang2018ccnet,
    title={CCNet: Criss-Cross Attention for Semantic Segmentation},
    author={Huang, Zilong and Wang, Xinggang and Huang, Lichao and Huang, Chang and Wei, Yunchao and Liu, Wenyu},
    booktitle={ICCV},
    year={2019}
}

Results and models

Cityscapes

Method	Backbone	Crop Size	Lr schd	Mem (GB)	Inf time (fps)	mIoU	mIoU(ms+flip)	download
CCNet	R-50-D8	512x1024	40000	6	3.32	77.76	78.87	model | log
CCNet	R-101-D8	512x1024	40000	9.5	2.31	76.35	78.19	model | log
CCNet	R-50-D8	769x769	40000	6.8	1.43	78.46	79.93	model | log
CCNet	R-101-D8	769x769	40000	10.7	1.01	76.94	78.62	model | log
CCNet	R-50-D8	512x1024	80000	-	-	79.03	80.16	model | log
CCNet	R-101-D8	512x1024	80000	-	-	78.87	79.90	model | log
CCNet	R-50-D8	769x769	80000	-	-	79.29	81.08	model | log
CCNet	R-101-D8	769x769	80000	-	-	79.45	80.66	model | log

ADE20K

Method	Backbone	Crop Size	Lr schd	Mem (GB)	Inf time (fps)	mIoU	mIoU(ms+flip)	download
CCNet	R-50-D8	512x512	80000	8.8	20.89	41.78	42.98	model | log
CCNet	R-101-D8	512x512	80000	12.2	14.11	43.97	45.13	model | log
CCNet	R-50-D8	512x512	160000	-	-	42.08	43.13	model | log
CCNet	R-101-D8	512x512	160000	-	-	43.71	45.04	model | log

Pascal VOC 2012 + Aug

Method	Backbone	Crop Size	Lr schd	Mem (GB)	Inf time (fps)	mIoU	mIoU(ms+flip)	download
CCNet	R-50-D8	512x512	20000	6	20.45	76.17	77.51	model | log
CCNet	R-101-D8	512x512	20000	9.5	13.64	77.27	79.02	model | log
CCNet	R-50-D8	512x512	40000	-	-	75.96	77.04	model | log
CCNet	R-101-D8	512x512	40000	-	-	77.87	78.90	model | log