Awesome
ShuffleNet Series
ShuffleNet Series by Megvii Research.
Introduction
This repository contains the following ShuffleNet series models:
- ShuffleNetV1: ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
- ShuffleNetV2: ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design
- ShuffleNetV2+: A strengthen version of ShuffleNetV2.
- ShuffleNetV2.Large: A deeper version based on ShuffleNetV2 with 10G+ FLOPs.
- ShuffleNetV2.ExLarge: A deeper version based on ShuffleNetV2 with 40G+ FLOPs.
- OneShot: Single Path One-Shot Neural Architecture Search with Uniform Sampling
- DetNAS: DetNAS: Backbone Search for Object Detection
Trained Models
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 |
ShuffleNetV2.ExLarge
The following is the result of ShuffleNetV2.ExLarge. Details can be seen in ShuffleNetV2.ExLarge.
Model | FLOPs | #Params | Top-1 | Top-5 |
---|---|---|---|---|
ShuffleNetV2.ExLarge | 46.2G | 254.7M | 15.52 | 2.9 |
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 backbones on ImageNet, compared with ResNet. Backbone details can be seen in DetNAS.
Model | FLOPs | #Params | Top-1 | Top-5 | mAP* |
---|---|---|---|---|---|
300M (VOC, RetinaNet) | 300M | 3.5M | 25.4 | 8.1 | 80.1 |
300M (VOC, FPN) | 300M | 3.7M | 25.9 | 8.3 | 81.5 |
300M (COCO, RetinaNet) | 300M | 3.7M | 26.0 | 8.4 | 33.3 |
300M (COCO, FPN) | 300M | 3.5M | 26.2 | 8.4 | 36.4 |
1.3G (COCO, FPN) | 1.3G | 10.4M | 22.8 | 6.5 | 40.0 |
3.8G (COCO, FPN) | 3.8G | 29.5M | 21.6 | 6.3 | 42.0 |
ResNet50 (COCO, FPN) | 3.8G | - | 23.9 | 7.1 | 37.3 |
ResNet101 (COCO, FPN) | 7.6G | - | 22.6 | 6.4 | 40.0 |
- More about DetNAS in Link.