fcn

Fully Convolutional Networks for Semantic Segmentation

Introduction

@article{shelhamer2017fully,
  title={Fully convolutional networks for semantic segmentation},
  author={Shelhamer, Evan and Long, Jonathan and Darrell, Trevor},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  volume={39},
  number={4},
  pages={640--651},
  year={2017},
  publisher={IEEE Trans Pattern Anal Mach Intell}
}

Results and models

Cityscapes

Method	Backbone	Crop Size	Lr schd	Mem (GB)	Inf time (fps)	mIoU	mIoU(ms+flip)	config	download
FCN	R-50-D8	512x1024	40000	5.7	4.17	72.25	73.36	config	model | log
FCN	R-101-D8	512x1024	40000	9.2	2.66	75.45	76.58	config	model | log
FCN	R-50-D8	769x769	40000	6.5	1.80	71.47	72.54	config	model | log
FCN	R-101-D8	769x769	40000	10.4	1.19	73.93	75.14	config	model | log
FCN	R-18-D8	512x1024	80000	1.7	14.65	71.11	72.91	config	model | log
FCN	R-50-D8	512x1024	80000	-		73.61	74.24	config	model | log
FCN	R-101-D8	512x1024	80000	-	-	75.13	75.94	config	model | log
FCN	R-18-D8	769x769	80000	1.9	6.40	70.80	73.16	config	model | log
FCN	R-50-D8	769x769	80000	-	-	72.64	73.32	config	model | log
FCN	R-101-D8	769x769	80000	-	-	75.52	76.61	config	model | log
FCN	R-18b-D8	512x1024	80000	1.6	16.74	70.24	72.77	config	model | log
FCN	R-50b-D8	512x1024	80000	5.6	4.20	75.65	77.59	config	model | log
FCN	R-101b-D8	512x1024	80000	9.1	2.73	77.37	78.77	config	model | log
FCN	R-18b-D8	769x769	80000	1.7	6.70	69.66	72.07	config	model | log
FCN	R-50b-D8	769x769	80000	6.3	1.82	73.83	76.60	config	model | log
FCN	R-101b-D8	769x769	80000	10.3	1.15	77.02	78.67	config	model | log
FCN-D6	R-50-D16	512x1024	40000	3.4	10.22	77.06	78.85	config	model | log
FCN-D6	R-50-D16	512x1024	80000	-	10.35	77.27	78.88	config	model | log
FCN-D6	R-50-D16	769x769	40000	3.7	4.17	76.82	78.22	config	model | log
FCN-D6	R-50-D16	769x769	80000	-	4.15	77.04	78.40	config	model | log
FCN-D6	R-101-D16	512x1024	40000	4.5	8.04	77.36	79.18	config	model | log
FCN-D6	R-101-D16	512x1024	80000	-	8.26	78.46	80.42	config	model | log
FCN-D6	R-101-D16	769x769	40000	5.0	3.12	77.28	78.95	config	model | log
FCN-D6	R-101-D16	769x769	80000	-	3.21	78.06	79.58	config	model | log
FCN-D6	R-50b-D16	512x1024	80000	3.2	10.16	76.99	79.03	config	model | log
FCN-D6	R-50b-D16	769x769	80000	3.6	4.17	76.86	78.52	config	model | log
FCN-D6	R-101b-D16	512x1024	80000	4.3	8.46	77.72	79.53	config	model | log
FCN-D6	R-101b-D16	769x769	80000	4.8	3.32	77.34	78.91	config	model | log

ADE20K

Method	Backbone	Crop Size	Lr schd	Mem (GB)	Inf time (fps)	mIoU	mIoU(ms+flip)	config	download
FCN	R-50-D8	512x512	80000	8.5	23.49	35.94	37.94	config	model | log
FCN	R-101-D8	512x512	80000	12	14.78	39.61	40.83	config	model | log
FCN	R-50-D8	512x512	160000	-	-	36.10	38.08	config	model | log
FCN	R-101-D8	512x512	160000	-	-	39.91	41.40	config	model | log

Pascal VOC 2012 + Aug

Method	Backbone	Crop Size	Lr schd	Mem (GB)	Inf time (fps)	mIoU	mIoU(ms+flip)	config	download
FCN	R-50-D8	512x512	20000	5.7	23.28	67.08	69.94	config	model | log
FCN	R-101-D8	512x512	20000	9.2	14.81	71.16	73.57	config	model | log
FCN	R-50-D8	512x512	40000	-	-	66.97	69.04	config	model | log
FCN	R-101-D8	512x512	40000	-	-	69.91	72.38	config	model | log

Pascal Context

Method	Backbone	Crop Size	Lr schd	Mem (GB)	Inf time (fps)	mIoU	mIoU(ms+flip)	config	download
FCN	R-101-D8	480x480	40000	-	9.93	44.43	45.63	config	model | log
FCN	R-101-D8	480x480	80000	-	-	44.13	45.26	config	model | log

Pascal Context 59

Method	Backbone	Crop Size	Lr schd	Mem (GB)	Inf time (fps)	mIoU	mIoU(ms+flip)	config	download
FCN	R-101-D8	480x480	40000	-	-	48.42	50.4	config	model | log
FCN	R-101-D8	480x480	80000	-	-	49.35	51.38	config	model | log