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Image classification and segmentation models for Chainer

Project description

Computer vision models on Chainer

PyPI Downloads

This is a collection of image classification and segmentation models. Many of them are pretrained on ImageNet-1K, CIFAR-10/100, SVHN, Pascal VOC2012, ADE20K, Cityscapes, and COCO datasets and loaded automatically during use. All pretrained models require the same ordinary normalization. Scripts for training/evaluating/converting models are in the imgclsmob repo.

List of implemented models

Installation

To use the models in your project, simply install the chainercv2 package:

pip install chainercv2

To enable/disable different hardware supports, check out Chainer installation instructions.

Usage

Example of using a pretrained ResNet-18 model:

from chainercv2.model_provider import get_model as chcv2_get_model
import numpy as np

net = chcv2_get_model("resnet18", pretrained=True)
x = np.zeros((1, 3, 224, 224), np.float32)
y = net(x)

Pretrained models

ImageNet-1K

Some remarks:

  • Top1/Top5 are the standard 1-crop Top-1/Top-5 errors (in percents) on the validation subset of the ImageNet-1K dataset.
  • FLOPs/2 is the number of FLOPs divided by two to be similar to the number of MACs.
  • Remark Converted from GL model means that the model was trained on MXNet/Gluon and then converted to Chainer.
  • ResNet(D) is a dilated ResNet intended for use as an feature extractor in some segmentation networks.
Model Top1 Top5 Params FLOPs/2 Remarks
AlexNet 44.08 21.32 61,100,840 714.83M From dmlc/gluon-cv (log)
VGG-11 31.89 11.79 132,863,336 7,615.87M From dmlc/gluon-cv (log)
VGG-13 31.06 11.16 133,047,848 11,317.65M From dmlc/gluon-cv (log)
VGG-16 26.75 8.70 138,357,544 15,480.10M From dmlc/gluon-cv (log)
VGG-19 25.86 8.23 143,667,240 19,642.55M From dmlc/gluon-cv (log)
BN-VGG-11b 30.37 10.60 132,868,840 7,630.72M From dmlc/gluon-cv (log)
BN-VGG-13b 29.45 10.19 133,053,736 11,342.14M From dmlc/gluon-cv (log)
BN-VGG-16b 26.89 8.63 138,365,992 15,507.20M From dmlc/gluon-cv (log)
BN-VGG-19b 25.65 8.16 143,678,248 19,672.26M From dmlc/gluon-cv (log)
BN-Inception 25.08 7.78 11,295,240 2,048.06M From Cadene/pretrained...pytorch (log)
ResNet-10 34.69 13.89 5,418,792 894.04M Converted from GL model (log)
ResNet-12 33.40 13.02 5,492,776 1,126.25M Converted from GL model (log)
ResNet-14 32.22 12.25 5,788,200 1,357.94M Converted from GL model (log)
ResNet-16 30.21 10.89 6,968,872 1,589.34M Converted from GL model (log)
ResNet-18 x0.25 39.32 17.45 3,937,400 270.94M Converted from GL model (log)
ResNet-18 x0.5 33.41 12.85 5,804,296 608.70M Converted from GL model (log)
ResNet-18 x0.75 29.98 10.67 8,476,056 1,129.45M Converted from GL model (log)
ResNet-18 28.08 9.59 11,689,512 1,820.41M Converted from GL model (log)
ResNet-26 26.14 8.36 17,960,232 2,746.79M Converted from GL model (log)
ResNet-34 24.51 7.46 21,797,672 3,672.68M Converted from GL model (log)
ResNet-50 22.61 6.41 25,557,032 3,877.95M From dmlc/gluon-cv (log)
ResNet-50b 22.08 6.15 25,557,032 4,110.48M Converted from GL model (log)
ResNet-101 21.65 6.01 44,549,160 7,597.95M From dmlc/gluon-cv (log)
ResNet-101b 20.79 5.40 44,549,160 7,830.48M From dmlc/gluon-cv (log)
ResNet-152 20.74 5.35 60,192,808 11,321.85M From dmlc/gluon-cv (log)
ResNet-152b 20.29 5.27 60,192,808 11,554.38M From dmlc/gluon-cv (log)
PreResNet-10 34.70 14.02 5,417,128 894.19M Converted from GL model (log)
PreResNet-12 33.62 13.18 5,491,112 1,126.40M Converted from GL model (log)
PreResNet-14 32.28 12.24 5,786,536 1,358.09M Converted from GL model (log)
PreResNet-16 30.22 10.80 6,967,208 1,589.49M Converted from GL model (log)
PreResNet-18 x0.25 39.58 17.78 3,935,960 270.93M Converted from GL model (log)
PreResNet-18 x0.5 33.64 13.12 5,802,440 608.73M Converted from GL model (log)
PreResNet-18 x0.75 29.95 10.69 8,473,784 1,129.51M Converted from GL model (log)
PreResNet-18 28.17 9.54 11,687,848 1,820.56M Converted from GL model (log)
PreResNet-34 24.58 7.55 21,796,008 3,672.83M Converted from GL model (log)
PreResNet-50 23.36 6.69 25,549,480 3,875.44M From dmlc/gluon-cv (log)
PreResNet-50b 22.31 6.34 25,549,480 4,107.97M Converted from GL model (log)
PreResNet-101 21.45 5.75 44,541,608 7,595.44M From dmlc/gluon-cv (log)
PreResNet-101b 21.61 5.87 44,541,608 7,827.97M From dmlc/gluon-cv (log)
PreResNet-152 20.73 5.30 60,185,256 11,319.34M From dmlc/gluon-cv (log)
PreResNet-152b 20.88 5.66 60,185,256 11,551.87M From dmlc/gluon-cv (log)
PreResNet-200b 21.03 5.60 64,666,280 15,068.63M From tornadomeet/ResNet (log)
PreResNet-269b 20.73 5.58 102,065,832 20,101.11M From soeaver/mxnet-model (log)
ResNeXt-101 (32x4d) 21.11 5.69 44,177,704 8,003.45M From Cadene/pretrained...pytorch (log)
ResNeXt-101 (64x4d) 20.57 5.43 83,455,272 15,500.27M From Cadene/pretrained...pytorch (log)
SE-ResNet-50 22.53 6.41 28,088,024 3,880.49M From Cadene/pretrained...pytorch (log)
SE-ResNet-101 21.90 5.88 49,326,872 7,602.76M From Cadene/pretrained...pytorch (log)
SE-ResNet-152 21.46 5.77 66,821,848 11,328.52M From Cadene/pretrained...pytorch (log)
SE-ResNeXt-50 (32x4d) 21.04 5.58 27,559,896 4,258.40M From Cadene/pretrained...pytorch (log)
SE-ResNeXt-101 (32x4d) 19.99 5.01 48,955,416 8,008.26M From Cadene/pretrained...pytorch (log)
SENet-154 18.79 4.63 115,088,984 20,745.78M From Cadene/pretrained...pytorch (log)
AirNet50-1x64d (r=2) 22.46 6.20 27,425,864 4,772.11M From soeaver/AirNet-PyTorch (log)
AirNet50-1x64d (r=16) 22.89 6.50 25,714,952 4,399.97M From soeaver/AirNet-PyTorch (log)
AirNeXt50-32x4d (r=2) 21.50 5.73 27,604,296 5,339.58M From soeaver/AirNet-PyTorch (log)
BAM-ResNet-50 23.71 6.97 25,915,099 4,196.09M From Jongchan/attention-module (log)
CBAM-ResNet-50 22.99 6.40 28,089,624 4,116.97M From Jongchan/attention-module (log)
PyramidNet-101 (a=360) 22.66 6.49 42,455,070 8,743.54M From dyhan0920/Pyramid...PyTorch (log)
DiracNetV2-18 30.60 11.13 11,511,784 1,796.62M From szagoruyko/diracnets (log)
DiracNetV2-34 27.90 9.48 21,616,232 3,646.93M From szagoruyko/diracnets (log)
DenseNet-121 25.04 7.79 7,978,856 2,872.13M From dmlc/gluon-cv (log)
DenseNet-161 22.36 6.20 28,681,000 7,793.16M From dmlc/gluon-cv (log)
DenseNet-169 23.85 6.86 14,149,480 3,403.89M From dmlc/gluon-cv (log)
DenseNet-201 22.64 6.29 20,013,928 4,347.15M From dmlc/gluon-cv (log)
CondenseNet-74 (C=G=4) 26.81 8.61 4,773,944 546.06M From ShichenLiu/CondenseNet (log)
CondenseNet-74 (C=G=8) 29.74 10.43 2,935,416 291.52M From ShichenLiu/CondenseNet (log)
PeleeNet 31.61 11.27 2,802,248 514.87M Converted from GL model (log)
WRN-50-2 22.06 6.13 68,849,128 11,405.42M From szagoruyko/functional-zoo (log)
DRN-C-26 25.68 7.88 21,126,584 16,993.90M From fyu/drn (log)
DRN-C-42 23.72 6.93 31,234,744 25,093.75M From fyu/drn (log)
DRN-C-58 22.35 6.29 40,542,008 32,489.94M From fyu/drn (log)
DRN-D-22 26.65 8.50 16,393,752 13,051.33M From fyu/drn (log)
DRN-D-38 24.53 7.36 26,501,912 21,151.19M From fyu/drn (log)
DRN-D-54 22.08 6.23 35,809,176 28,547.38M From fyu/drn (log)
DRN-D-105 21.32 5.84 54,801,304 43,442.43M From fyu/drn (log)
DPN-68 23.61 7.01 12,611,602 2,351.84M From Cadene/pretrained...pytorch (log)
DPN-98 20.80 5.53 61,570,728 11,716.51M From Cadene/pretrained...pytorch (log)
DPN-131 20.04 5.23 79,254,504 16,076.15M From Cadene/pretrained...pytorch (log)
DarkNet Tiny 40.33 17.46 1,042,104 500.85M Converted from GL model (log)
DarkNet Ref 38.09 16.71 7,319,416 367.59M Converted from GL model (log)
DarkNet-53 21.41 5.56 41,609,928 7,133.86M From dmlc/gluon-cv (log)
i-RevNet-301 26.96 8.87 125,120,356 14,453.87M From jhjacobsen/pytorch-i-revnet (log)
BagNet-9 59.57 35.45 15,688,744 16,049.19M From wielandbrendel/bag...models (log)
BagNet-17 44.78 21.51 16,213,032 15,768.77M From wielandbrendel/bag...models (log)
BagNet-33 36.41 14.92 18,310,184 16,371.52M From wielandbrendel/bag...models (log)
DLA-34 26.14 8.23 15,742,104 3,071.37M From ucbdrive/dla (log)
DLA-46-C 33.85 12.92 1,301,400 585.45M Converted from GL model (log)
DLA-X-46-C 32.90 12.28 1,068,440 546.72M Converted from GL model (log)
DLA-60 23.78 7.11 22,036,632 4,255.49M From ucbdrive/dla (log)
DLA-X-60 22.46 6.20 17,352,344 3,543.68M From ucbdrive/dla (log)
DLA-X-60-C 30.70 10.76 1,319,832 596.06M Converted from GL model (log)
DLA-102 22.87 6.42 33,268,888 7,190.95M From ucbdrive/dla (log)
DLA-X-102 21.93 5.99 26,309,272 5,884.94M From ucbdrive/dla (log)
DLA-X2-102 21.11 5.54 41,282,200 9,340.61M From ucbdrive/dla (log)
DLA-169 21.99 5.90 53,389,720 11,593.20M From ucbdrive/dla (log)
FishNet-150 22.86 6.39 24,959,400 6,435.05M From kevin-ssy/FishNet (log)
ESPNetv2 x0.5 43.61 21.08 1,241,332 35.36M From sacmehta/ESPNetv2 (log)
ESPNetv2 x1.0 35.30 14.31 1,670,072 98.09M From sacmehta/ESPNetv2 (log)
ESPNetv2 x1.25 33.07 12.68 1,965,440 138.18M From sacmehta/ESPNetv2 (log)
ESPNetv2 x1.5 31.96 11.92 2,314,856 185.77M From sacmehta/ESPNetv2 (log)
ESPNetv2 x2.0 28.95 9.90 3,498,136 306.93M From sacmehta/ESPNetv2 (log)
SqueezeNet v1.0 38.76 17.38 1,248,424 823.67M Converted from GL model (log)
SqueezeNet v1.1 39.13 17.40 1,235,496 352.02M Converted from GL model (log)
SqueezeResNet v1.0 39.36 17.66 1,248,424 823.67M Converted from GL model (log)
SqueezeResNet v1.1 39.85 17.87 1,235,496 352.02M Converted from GL model (log)
1.0-SqNxt-23 42.62 19.03 724,056 287.28M Converted from GL model (log)
1.0-SqNxt-23v5 40.96 17.86 921,816 285.82M Converted from GL model (log)
1.5-SqNxt-23 34.71 13.44 1,511,824 552.39M Converted from GL model (log)
1.5-SqNxt-23v5 33.79 12.92 1,953,616 550.97M Converted from GL model (log)
2.0-SqNxt-23 30.43 10.82 2,583,752 898.48M Converted from GL model (log)
2.0-SqNxt-23v5 29.58 10.43 3,366,344 897.60M Converted from GL model (log)
ShuffleNet x0.25 (g=1) 62.04 36.81 209,746 12.35M Converted from GL model (log)
ShuffleNet x0.25 (g=3) 61.30 36.16 305,902 13.09M Converted from GL model (log)
ShuffleNet x0.5 (g=1) 46.24 22.35 534,484 41.16M Converted from GL model (log)
ShuffleNet x0.5 (g=3) 43.83 20.61 718,324 41.70M Converted from GL model (log)
ShuffleNet x0.75 (g=1) 39.26 16.77 975,214 86.42M Converted from GL model (log)
ShuffleNet x0.75 (g=3) 37.83 16.13 1,238,266 85.82M Converted from GL model (log)
ShuffleNet x1.0 (g=1) 34.44 13.48 1,531,936 148.13M Converted from GL model (log)
ShuffleNet x1.0 (g=2) 33.94 13.33 1,733,848 147.60M Converted from GL model (log)
ShuffleNet x1.0 (g=3) 33.99 13.26 1,865,728 145.46M Converted from GL model (log)
ShuffleNet x1.0 (g=4) 33.87 13.08 1,968,344 143.33M Converted from GL model (log)
ShuffleNet x1.0 (g=8) 33.68 13.21 2,434,768 150.76M Converted from GL model (log)
ShuffleNetV2 x0.5 43.45 20.73 1,366,792 43.31M Converted from GL model (log)
ShuffleNetV2 x1.0 33.39 12.98 2,278,604 149.72M Converted from GL model (log)
ShuffleNetV2 x1.5 28.87 10.14 4,406,098 320.77M Converted from GL model (log)
ShuffleNetV2 x2.0 27.01 8.99 7,601,686 595.84M Converted from GL model (log)
ShuffleNetV2b x0.5 39.78 17.87 1,366,792 43.31M Converted from GL model (log)
ShuffleNetV2b x1.0 30.36 11.00 2,279,760 150.62M Converted from GL model (log)
ShuffleNetV2b x1.5 26.92 8.78 4,410,194 323.98M Converted from GL model (log)
ShuffleNetV2b x2.0 25.23 8.10 7,611,290 603.37M Converted from GL model (log)
108-MENet-8x1 (g=3) 43.67 20.42 654,516 42.68M Converted from GL model (log)
128-MENet-8x1 (g=4) 42.07 19.19 750,796 45.98M Converted from GL model (log)
160-MENet-8x1 (g=8) 43.54 20.42 850,120 45.63M Converted from GL model (log)
228-MENet-12x1 (g=3) 33.86 13.01 1,806,568 152.93M Converted from GL model (log)
256-MENet-12x1 (g=4) 32.30 12.18 1,888,240 150.65M Converted from GL model (log)
348-MENet-12x1 (g=3) 27.86 9.36 3,368,128 312.00M Converted from GL model (log)
352-MENet-12x1 (g=8) 31.28 11.72 2,272,872 157.35M Converted from GL model (log)
456-MENet-24x1 (g=3) 25.07 7.79 5,304,784 567.90M Converted from GL model (log)
MobileNet x0.25 45.85 22.16 470,072 44.09M Converted from GL model (log)
MobileNet x0.5 33.89 13.37 1,331,592 155.42M Converted from GL model (log)
MobileNet x0.75 29.86 10.53 2,585,560 333.99M Converted from GL model (log)
MobileNet x1.0 26.47 8.66 4,231,976 579.80M Converted from GL model (log)
FD-MobileNet x0.25 55.43 30.63 383,160 12.95M Converted from GL model (log)
FD-MobileNet x0.5 42.68 19.76 993,928 41.84M Converted from GL model (log)
FD-MobileNet x0.75 37.94 15.99 1,833,304 86.68M Converted from GL model (log)
FD-MobileNet x1.0 33.90 13.16 2,901,288 147.46M Converted from GL model (log)
MobileNetV2 x0.25 48.10 24.11 1,516,392 34.24M Converted from GL model (log)
MobileNetV2 x0.5 35.56 14.44 1,964,736 100.13M Converted from GL model (log)
MobileNetV2 x0.75 29.75 10.47 2,627,592 198.50M Converted from GL model (log)
MobileNetV2 x1.0 26.80 8.66 3,504,960 329.36M Converted from GL model (log)
IGCV3 x0.25 53.36 28.28 1,534,020 41.29M Converted from GL model (log)
IGCV3 x0.5 39.36 17.04 1,985,528 111.12M Converted from GL model (log)
IGCV3 x0.75 30.67 10.99 2,638,084 210.95M Converted from GL model (log)
IGCV3 x1.0 27.70 8.98 3,491,688 340.79M Converted from GL model (log)
MnasNet 31.27 11.44 4,308,816 317.67M From zeusees/Mnasnet...Model (log)
DARTS 27.29 8.97 4,718,752 539.86M From quark0/darts (log)
ProxylessNAS CPU 25.35 7.83 4,361,648 459.96M From MIT-HAN-LAB/ProxylessNAS (log)
ProxylessNAS GPU 25.53 7.79 7,119,848 476.08M From MIT-HAN-LAB/ProxylessNAS (log)
ProxylessNAS Mobile 26.19 8.19 4,080,512 332.46M From MIT-HAN-LAB/ProxylessNAS (log)
ProxylessNAS Mobile-14 24.01 6.86 6,857,568 597.10M From MIT-HAN-LAB/ProxylessNAS (log)
Xception 21.04 5.47 22,855,952 8,403.63M From Cadene/pretrained...pytorch (log)
InceptionV3 21.11 5.61 23,834,568 5,743.06M From dmlc/gluon-cv (log)
InceptionV4 20.62 5.26 42,679,816 12,304.93M From Cadene/pretrained...pytorch (log)
InceptionResNetV2 19.93 4.92 55,843,464 13,188.64M From Cadene/pretrained...pytorch (log)
PolyNet 19.08 4.50 95,366,600 34,821.34M From Cadene/pretrained...pytorch (log)
NASNet-A 4@1056 25.36 7.96 5,289,978 584.90M From Cadene/pretrained...pytorch (log)
NASNet-A 6@4032 18.17 4.22 88,753,150 23,976.44M From Cadene/pretrained...pytorch (log)
PNASNet-5-Large 17.90 4.26 86,057,668 25,140.77M From Cadene/pretrained...pytorch (log)
ResNet(D)-50b 20.80 5.50 25,680,808 20,497.60M From dmlc/gluon-cv (log)
ResNet(D)-101b 19.49 4.60 44,672,936 35,392.65M From dmlc/gluon-cv (log)
ResNet(D)-152b 19.36 4.70 60,316,584 47,662.18M From dmlc/gluon-cv (log)

CIFAR-10

Model Error, % Params FLOPs/2 Remarks
NIN 7.43 966,986 222.97M Converted from GL model (log)
ResNet-20 5.97 272,474 41.29M Converted from GL model (log)
ResNet-56 4.52 855,770 127.06M Converted from GL model (log)
ResNet-110 3.69 1,730,714 255.70M Converted from GL model (log)
ResNet-164(BN) 3.68 1,704,154 255.31M Converted from GL model (log)
ResNet-1001 3.28 10,328,602 1,536.40M Converted from GL model (log)
ResNet-1202 3.53 19,424,026 2,857.17M Converted from GL model (log)
PreResNet-20 6.51 272,282 41.27M Converted from GL model (log)
PreResNet-56 4.49 855,578 127.03M Converted from GL model (log)
PreResNet-110 3.86 1,730,522 255.68M Converted from GL model (log)
PreResNet-164(BN) 3.64 1,703,258 255.08M Converted from GL model (log)
PreResNet-1001 2.65 10,327,706 1,536.18M Converted from GL model (log)
PreResNet-1202 3.39 19,423,834 2,857.14M Converted from GL model (log)
ResNeXt-29 (32x4d) 3.15 4,775,754 780.55M Converted from GL model (log)
ResNeXt-29 (16x64d) 2.41 68,155,210 10,709.34M Converted from GL model (log)
PyramidNet-110 (a=48) 3.72 1,772,706 408.37M Converted from GL model (log)
PyramidNet-110 (a=84) 2.98 3,904,446 778.15M Converted from GL model (log)
PyramidNet-110 (a=270) 2.51 28,485,477 4,730.60M Converted from GL model (log)
PyramidNet-164 (a=270, BN) 2.42 27,216,021 4,608.81M Converted from GL model (log)
PyramidNet-200 (a=240, BN) 2.44 26,752,702 4,563.40M Converted from GL model (log)
PyramidNet-236 (a=220, BN) 2.47 26,969,046 4,631.32M Converted from GL model (log)
PyramidNet-272 (a=200, BN) 2.39 26,210,842 4,541.36M Converted from GL model (log)
DenseNet-40 (k=12) 5.61 599,050 210.80M Converted from GL model (log)
DenseNet-BC-40 (k=12) 6.43 176,122 74.89M Converted from GL model (log)
DenseNet-BC-40 (k=24) 4.52 690,346 293.09M Converted from GL model (log)
DenseNet-BC-40 (k=36) 4.04 1,542,682 654.60M Converted from GL model (log)
DenseNet-100 (k=12) 3.66 4,068,490 1,353.55M Converted from GL model (log)
DenseNet-100 (k=24) 3.13 16,114,138 5,354.19M Converted from GL model (log)
DenseNet-BC-100 (k=12) 4.16 769,162 298.45M Converted from GL model (log)
DenseNet-BC-190 (k=40) 2.52 25,624,430 9,400.45M Converted from GL model (log)
DenseNet-BC-250 (k=24) 2.67 15,324,406 5,519.54M Converted from GL model (log)
X-DenseNet-BC-40-2 (k=24) 5.31 690,346 293.09M Converted from GL model (log)
X-DenseNet-BC-40-2 (k=36) 4.37 1,542,682 654.60M Converted from GL model (log)
WRN-16-10 2.93 17,116,634 2,414.04M Converted from GL model (log)
WRN-28-10 2.39 36,479,194 5,246.98M Converted from GL model (log)
WRN-40-8 2.37 35,748,314 5,176.90M Converted from GL model (log)
WRN-20-10-1bit 3.26 26,737,140 4,019.14M Converted from GL model (log)
WRN-20-10-32bit 3.14 26,737,140 4,019.14M Converted from GL model (log)
RoR-3-56 5.43 762,746 113.43M Converted from GL model (log)
RoR-3-110 4.35 1,637,690 242.07M Converted from GL model (log)
RoR-3-164 3.93 2,512,634 370.72M Converted from GL model (log)
RiR 3.28 9,492,980 1,281.08M Converted from GL model (log)
Shake-Shake-ResNet-20-2x16d 5.15 541,082 81.78M Converted from GL model (log)
Shake-Shake-ResNet-26-2x32d 3.17 2,923,162 428.89M Converted from GL model (log)

CIFAR-100

Model Error, % Params FLOPs/2 Remarks
NIN 28.39 984,356 224.08M Converted from GL model (log)
ResNet-20 29.64 278,324 41.30M Converted from GL model (log)
ResNet-56 24.88 861,620 127.06M Converted from GL model (log)
ResNet-110 22.80 1,736,564 255.71M Converted from GL model (log)
ResNet-164(BN) 20.44 1,727,284 255.33M Converted from GL model (log)
ResNet-1001 19.79 10,351,732 1,536.43M Converted from GL model (log)
PreResNet-20 30.22 278,132 41.28M Converted from GL model (log)
PreResNet-56 25.05 861,428 127.04M Converted from GL model (log)
PreResNet-110 22.67 1,736,372 255.68M Converted from GL model (log)
PreResNet-164(BN) 20.18 1,726,388 255.10M Converted from GL model (log)
PreResNet-1001 18.41 10,350,836 1,536.20M Converted from GL model (log)
ResNeXt-29 (32x4d) 19.50 4,868,004 780.64M Converted from GL model (log)
PyramidNet-110 (a=48) 20.95 1,778,556 408.38M Converted from GL model (log)
PyramidNet-110 (a=84) 18.87 3,913,536 778.16M Converted from GL model (log)
DenseNet-40 (k=12) 24.90 622,360 210.82M Converted from GL model (log)
DenseNet-BC-40 (k=12) 28.41 188,092 74.90M Converted from GL model (log)
DenseNet-BC-40 (k=24) 22.67 714,196 293.11M Converted from GL model (log)
DenseNet-BC-40 (k=36) 20.50 1,578,412 654.64M Converted from GL model (log)
DenseNet-100 (k=12) 19.64 4,129,600 1,353.62M Converted from GL model (log)
DenseNet-BC-100 (k=12) 21.19 800,032 298.48M Converted from GL model (log)
DenseNet-BC-250 (k=24) 17.39 15,480,556 5,519.69M Converted from GL model (log)
X-DenseNet-BC-40-2 (k=24) 23.96 714,196 293.11M Converted from GL model (log)
X-DenseNet-BC-40-2 (k=36) 21.65 1,578,412 654.64M Converted from GL model (log)
WRN-16-10 18.95 17,174,324 2,414.09M Converted from GL model (log)
WRN-20-10-1bit 19.04 26,794,920 4,022.81M Converted from GL model (log)
WRN-20-10-32bit 18.12 26,794,920 4,022.81M Converted from GL model (log)
RoR-3-56 25.49 768,596 113.43M Converted from GL model (log)
RoR-3-110 23.64 1,643,540 242.08M Converted from GL model (log)
RoR-3-164 22.34 2,518,484 370.72M Converted from GL model (log)
RiR 19.23 9,527,720 1,283.29M Converted from GL model (log)
Shake-Shake-ResNet-20-2x16d 29.22 546,932 81.79M Converted from GL model (log)
Shake-Shake-ResNet-26-2x32d 18.80 2,934,772 428.90M Converted from GL model (log)

SVHN

Model Error, % Params FLOPs/2 Remarks
NIN 3.76 966,986 222.97M Converted from GL model (log)
ResNet-20 3.43 272,474 41.29M Converted from GL model (log)
ResNet-56 2.75 855,770 127.06M Converted from GL model (log)
ResNet-110 2.45 1,730,714 255.70M Converted from GL model (log)
ResNet-164(BN) 2.42 1,704,154 255.31M Converted from GL model (log)
PreResNet-20 3.22 272,282 41.27M Converted from GL model (log)
PreResNet-56 2.80 855,578 127.03M Converted from GL model (log)
PreResNet-110 2.79 1,730,522 255.68M Converted from GL model (log)
PreResNet-164(BN) 2.58 1,703,258 255.08M Converted from GL model (log)
ResNeXt-29 (32x4d) 2.80 4,775,754 780.55M Converted from GL model (log)
PyramidNet-110 (a=48) 2.47 1,772,706 408.37M Converted from GL model (log)
DenseNet-40 (k=12) 3.05 599,050 210.80M Converted from GL model (log)
DenseNet-BC-40 (k=12) 3.20 176,122 74.89M Converted from GL model (log)
DenseNet-BC-40 (k=24) 2.90 690,346 293.09M Converted from GL model (log)
X-DenseNet-BC-40-2 (k=24) 2.87 690,346 293.09M Converted from GL model (log)
X-DenseNet-BC-40-2 (k=36) 2.74 1,542,682 654.60M Converted from GL model (log)
WRN-16-10 2.78 17,116,634 2,414.04M Converted from GL model (log)
WRN-28-10 2.71 36,479,194 5,246.98M Converted from GL model (log)
WRN-40-8 2.54 35,748,314 5,176.90M Converted from GL model (log)
WRN-20-10-1bit 2.73 26,737,140 4,019.14M Converted from GL model (log)
WRN-20-10-32bit 2.59 26,737,140 4,019.14M Converted from GL model (log)
RoR-3-56 2.69 762,746 113.43M Converted from GL model (log)
RoR-3-110 2.57 1,637,690 242.07M Converted from GL model (log)
RoR-3-164 2.73 2,512,634 370.72M Converted from GL model (log)
RiR 2.68 9,492,980 1,281.08M Converted from GL model (log)
Shake-Shake-ResNet-20-2x16d 3.17 541,082 81.78M Converted from GL model (log)
Shake-Shake-ResNet-26-2x32d 2.62 2,923,162 428.89M Converted from GL model (log)

Pascal VOC20102

Model Extractor Pix.Acc., % mIoU, % Params FLOPs/2 Remarks
PSPNet ResNet(D)-101b 96.57 76.26 65,708,501 230,771.01M From dmlc/gluon-cv (log)
DeepLabv3 ResNet(D)-101b 96.57 75.66 58,754,773 47,625.34M From dmlc/gluon-cv (log)
DeepLabv3 ResNet(D)-152b 97.25 78.06 74,398,421 59,894.87M From dmlc/gluon-cv (log)
FCN-8s(d) ResNet(D)-101b 97.80 80.40 52,072,917 196,562.96M From dmlc/gluon-cv (log)

ADE20K

Model Extractor Pix.Acc., % mIoU, % Params FLOPs/2 Remarks
PSPNet ResNet(D)-50b 68.95 27.46 46,782,550 162,595.14M From dmlc/gluon-cv (log)
PSPNet ResNet(D)-101b 75.14 32.86 65,774,678 231,008.79M From dmlc/gluon-cv (log)
DeepLabv3 ResNet(D)-50b 74.63 31.96 39,795,798 32,756.18M From dmlc/gluon-cv (log)
DeepLabv3 ResNet(D)-101b 77.81 35.17 58,787,926 47,651.23M From dmlc/gluon-cv (log)
FCN-8s(d) ResNet(D)-50b 76.92 33.39 33,146,966 128,387.08M From dmlc/gluon-cv (log)
FCN-8s(d) ResNet(D)-101b 79.01 35.88 52,139,094 196,800.73M From dmlc/gluon-cv (log)

Cityscapes

Model Extractor Pix.Acc., % mIoU, % Params FLOPs/2 Remarks
PSPNet ResNet(D)-101b 92.72 57.57 65,707,475 230,767.33M From dmlc/gluon-cv (log)

COCO

Model Extractor Pix.Acc., % mIoU, % Params FLOPs/2 Remarks
PSPNet ResNet(D)-101b 88.99 54.67 65,708,501 230,771.01M From dmlc/gluon-cv (log)
DeepLabv3 ResNet(D)-101b 90.10 59.06 58,754,773 47,625.34M From dmlc/gluon-cv (log)
DeepLabv3 ResNet(D)-152b 90.52 61.07 74,398,421 275,087.91M From dmlc/gluon-cv (log)
FCN-8s(d) ResNet(D)-101b 91.44 60.11 52,072,917 196,562.96M From dmlc/gluon-cv (log)

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