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https://github.com/GuanRunwei/MAN-and-CAT
This is the official page of the object detection network: CAT-YOLO
https://github.com/GuanRunwei/MAN-and-CAT
Last synced: 3 months ago
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This is the official page of the object detection network: CAT-YOLO
- Host: GitHub
- URL: https://github.com/GuanRunwei/MAN-and-CAT
- Owner: GuanRunwei
- Created: 2022-03-27T07:15:17.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2022-09-24T06:40:32.000Z (over 2 years ago)
- Last Synced: 2024-08-02T01:22:25.635Z (7 months ago)
- Language: Python
- Size: 21 MB
- Stars: 26
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-yolo-object-detection - GuanRunwei/MAN-and-CAT - and-CAT?style=social"/> : "MAN and CAT: mix attention to nn and concatenate attention to YOLO". (**[ The Journal of Supercomputing, 2022](https://link.springer.com/article/10.1007/s11227-022-04726-7)**) (Applications)
- awesome-yolo-object-detection - GuanRunwei/MAN-and-CAT - and-CAT?style=social"/> : "MAN and CAT: mix attention to nn and concatenate attention to YOLO". (**[ The Journal of Supercomputing, 2022](https://link.springer.com/article/10.1007/s11227-022-04726-7)**) (Applications)
README
# MAN and CAT: Mix Attention to NN and Concatenate Attention to YOLO
===This is the official page of Mix Attention, MANet and CAT-YOLO===
## Benchmark Results
### Mix Attention Block with ResNet-101 and WRN-18 on CIFAR-10
Model
Params(M)
Top-1 Error(%)
ResNet-101 + Mix Attention
50.07
6.17
WRN-18 + Mix Attention
27.11
4.77
### Mix Attention Block with ResNet-101 and WRN-18 on CIFAR-100
Model
Params(M)
Top-1 Error(%)
ResNet-101 + Mix Attention
50.07
23.19
WRN-18 + Mix Attention
27.11
19.11
***
### MANet on ImageNet
Model
Params(M)
Top-1 Accuracy(%)
MANet-B
69.3
81.7
MANet-S
23.4
78.3
MANet-T
4.3
73.1
### MANet on CIFAR-10
Model
Params(M)
Top-1 Accuracy(%)
MANet-B
69.3
97.2
MANet-S
23.4
95.1
MANet-T
4.3
93.4
### MANet on CIFAR-100
Model
Params(M)
Top-1 Accuracy(%)
MANet-B
69.3
88.7
MANet-S
23.4
86.5
MANet-T
4.3
81.6
***
### CAT-YOLO on COCO 2017
Model
Backbone
Params(M)
Latency(ms)
AP
CAT-YOLO-v1
CSPDarknet53-Tiny
6.16
9.9(TITAN RTX)
24.1
CAT-YOLO-v2
MANet-T
9.17
12.7(TITAN RTX)
25.7
CAT-YOLO-v3
MANet-T
12.5
16.8(TITAN RTX)
33.5
***
## User Guide
### **MAN** includes the plug-and-play modules(Mix Attention) and backbone(MANet).
**Note**:
1. We divide the modules and backbones for [CIFAR](https://github.com/GuanRunwei/MAN-and-CAT/tree/main/MAN/Modules/For%20CIFAR) and [ImageNet](https://github.com/GuanRunwei/MAN-and-CAT/tree/main/MAN/Modules/For%20ImageNet_Like) respectively.
2. The sub-folder named "Big Version" in [Modules](https://github.com/GuanRunwei/MAN-and-CAT/tree/main/MAN/Modules) play the role of one individual layer.
3. The sub-folder named "Tiny Version" in [Modules](https://github.com/GuanRunwei/MAN-and-CAT/tree/main/MAN/Modules) play the role of the enhance module in the network's bottleneck.
### **CAT** includes the files of CAT-YOLO.
## Citation
@article{guan2022man,
title={MAN and CAT: mix attention to nn and concatenate attention to YOLO},
author={Guan, Runwei and Man, Ka Lok and Zhao, Haocheng and Zhang, Ruixiao and Yao, Shanliang and Smith, Jeremy and Lim, Eng Gee and Yue, Yutao},
journal={The Journal of Supercomputing},
pages={1--29},
year={2022},
publisher={Springer}
}