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ShuffleNet Series

ShuffleNet Series by Megvii Research.

Introduction

This repository contains the following ShuffleNet series models:

Trained Models

Details

ShuffleNetV2+

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

ModelFLOPs#ParamsTop-1Top-5
ShuffleNetV2+ Large360M6.7M22.96.7
MobileNetV3 Large 224/1.25356M7.5M23.4-
ShuffleNetV2+ Medium222M5.6M24.37.4
MobileNetV3 Large 224/1.0217M5.4M24.8-
ShuffleNetV2+ Small156M5.1M25.98.3
MobileNetV3 Large 224/0.75155M4.0M26.7-

ShuffleNetV2

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

ModelFLOPs#ParamsTop-1Top-5
ShuffleNetV2 2.0x591M7.4M25.07.6
MobileNetV2 (1.4)585M6.9M25.3-
ShuffleNetV2 1.5x299M3.5M27.49.4
MobileNetV2300M3.4M28.0-
ShuffleNetV2 1.0x146M2.3M30.611.1
ShuffleNetV2 0.5x41M1.4M38.917.4

ShuffleNetV2.Large

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

ModelFLOPs#ParamsTop-1Top-5
ShuffleNetV2.Large12.7G140.7M18.564.48
SENet20.7G-18.684.47

ShuffleNetV2.ExLarge

The following is the result of ShuffleNetV2.ExLarge. Details can be seen in ShuffleNetV2.ExLarge.

ModelFLOPs#ParamsTop-1Top-5
ShuffleNetV2.ExLarge46.2G254.7M15.522.9

ShuffleNetV1

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

ModelFLOPs#ParamsTop-1Top-5
ShuffleNetV1 2.0x (group=3)524M5.4M25.98.6
ShuffleNetV1 2.0x (group=8)522M6.5M27.19.2
1.0 MobileNetV1-224569M4.2M29.4-
ShuffleNetV1 1.5x (group=3)292M3.4M28.49.8
ShuffleNetV1 1.5x (group=8)290M4.3M29.010.4
0.75 MobileNetV1-224325M2.6M31.6-
ShuffleNetV1 1.0x (group=3)138M1.9M32.212.3
ShuffleNetV1 1.0x (group=8)138M2.4M32.013.6
0.5 MobileNetV1-224149M1.3M36.3-
ShuffleNetV1 0.5x (group=3)38M0.7M42.720.0
ShuffleNetV1 0.5x (group=8)40M1.0M41.219.0
0.25 MobileNetV1-22441M0.5M49.4-

OneShot

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

ModelFLOPs#ParamsTop-1Top-5
OneShot328M3.4M25.18.0
NASNET-A564M5.3M26.08.4
PNASNET588M5.1M25.88.1
MnasNet317M4.2M26.08.2
DARTS574M4.7M26.78.7
FBNet-B295M4.5M25.9-

DetNAS

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

ModelFLOPs#ParamsTop-1Top-5mAP*
300M (VOC, RetinaNet)300M3.5M25.48.180.1
300M (VOC, FPN)300M3.7M25.98.381.5
300M (COCO, RetinaNet)300M3.7M26.08.433.3
300M (COCO, FPN)300M3.5M26.28.436.4
1.3G (COCO, FPN)1.3G10.4M22.86.540.0
3.8G (COCO, FPN)3.8G29.5M21.66.342.0
ResNet50 (COCO, FPN)3.8G-23.97.137.3
ResNet101 (COCO, FPN)7.6G-22.66.440.0