/ShuffleNet-Series

Primary LanguagePythonMIT LicenseMIT

ShuffleNet Series

ShuffleNet Series by Megvii Research.

Introduction

This repository contains the following ShuffleNet series models:

Trained Models

OneDrive download: Link

Details

ShuffleNetV2+

The following is the comparison between ShuffleNetV2+ and MobileNetV3. Details can be seen in ShuffleNetV2+.

Model FLOPs #Params Top-1 Top-5
ShuffleNetV2+ Large 360M 6.7M 22.9 6.7
MobileNetV3 Large 224/1.25 356M 7.5M 23.4 -
ShuffleNetV2+ Medium 222M 5.6M 24.3 7.4
MobileNetV3 Large 224/1.0 217M 5.4M 24.8 -
ShuffleNetV2+ Small 156M 5.1M 25.9 8.3
MobileNetV3 Large 224/0.75 155M 4.0M 26.7 -

ShuffleNetV2

The following is the comparison between ShuffleNetV2 and MobileNetV2. Details can be seen in ShuffleNetV2.

Model FLOPs #Params Top-1 Top-5
ShuffleNetV2 2.0x 591M 7.4M 25.0 7.6
MobileNetV2 (1.4) 585M 6.9M 25.3 -
ShuffleNetV2 1.5x 299M 3.5M 27.4 9.4
MobileNetV2 300M 3.4M 28.0 -
ShuffleNetV2 1.0x 146M 2.3M 30.6 11.1
ShuffleNetV2 0.5x 41M 1.4M 38.9 17.4

ShuffleNetV2.Large

The following is the comparison between ShuffleNetV2.Large and SENet. Details can be seen in ShuffleNetV2.Large.

Model FLOPs #Params Top-1 Top-5
ShuffleNetV2.Large 12.7G 140.7M 18.56 4.48
SENet 20.7G - 18.68 4.47

ShuffleNetV1

The following is the comparison between ShuffleNetV1 and MobileNetV1. Details can be seen in ShuffleNetV1.

Model FLOPs #Params Top-1 Top-5
ShuffleNetV1 2.0x (group=3) 524M 5.4M 25.9 8.6
ShuffleNetV1 2.0x (group=8) 522M 6.5M 27.1 9.2
1.0 MobileNetV1-224 569M 4.2M 29.4 -
ShuffleNetV1 1.5x (group=3) 292M 3.4M 28.4 9.8
ShuffleNetV1 1.5x (group=8) 290M 4.3M 29.0 10.4
0.75 MobileNetV1-224 325M 2.6M 31.6 -
ShuffleNetV1 1.0x (group=3) 138M 1.9M 32.2 12.3
ShuffleNetV1 1.0x (group=8) 138M 2.4M 32.0 13.6
0.5 MobileNetV1-224 149M 1.3M 36.3 -
ShuffleNetV1 0.5x (group=3) 38M 0.7M 42.7 20.0
ShuffleNetV1 0.5x (group=8) 40M 1.0M 41.2 19.0
0.25 MobileNetV1-224 41M 0.5M 49.4 -

OneShot

The following is the comparison between Single Path One-Shot NAS and other NAS counterparts. Details can be seen in OneShot.

Model FLOPs #Params Top-1 Top-5
OneShot 328M 3.4M 25.1 8.0
NASNET-A 564M 5.3M 26.0 8.4
PNASNET 588M 5.1M 25.8 8.1
MnasNet 317M 4.2M 26.0 8.2
DARTS 574M 4.7M 26.7 8.7
FBNet-B 295M 4.5M 25.9 -

DetNAS

The following is the performance of DetNAS on ImageNet, compared with ResNet. Details can be seen in DetNAS.

Model FLOPs #Params Top-1 Top-5 mAP (COCO, FPN)*
DetNAS_small 300M 3.7M 25.9 8.3 36.4
DetNAS_medium 1.3G 10.4M 22.8 6.5 40.0
DetNAS_large 3.8G 29.5M 21.6 6.3 42.0
ResNet50 3.8G - 23.9 7.1 37.3
ResNet101 7.6G - 22.6 6.4 40.0

*COCO models are coming soon.