[TOC]
Reproduction of Peer Collaborative Learning for Online Knowledge Distillation in AAAI2021, the paper link is at here
- torch==1.5.1
- torchvision==0.6.1
- easydict==1.9
- tensorboard==2.4.1
- tensorboardX==2.1
- PyYAML==5.3.1
- Firstly, config your dataset root at
./src/datasets/dataset_config.yml
- run code (method 1)
python main.py --model resnet32 --save_dir cifar100_resnet32 --config_path ./configs/cifar100.yml
- or you can run code (method 2)
sh run_cifar100.sh
In our replementation, we recored the best accuracy score among the three peers, instead of the first peer in original paper. And we only report result over 1 run time.
all the replemetation training logs can be downloaded in package at pan.baidu code:k8ff
Network | DML | CL | ONE | FFL-S | OKDDip | KDCL | PCL | ours |
---|---|---|---|---|---|---|---|---|
ResNet-32 | 73.68±0.14 | 72.33±0.46 | 73.79±0.41 | 72.18±0.11 | 73.25±0.38 | 73.76±0.34 | 74.14±0.16 | 74.77 |
ResNet-110 | 77.86±0.50 | 78.83±0.58 | 78.40±0.36 | 77.22±0.41 | 78.54±0.26 | 78.28±0.32 | 79.98±0.55 | 79.07 |
VGG-16 | 75.52±0.10 | 74.33±0.08 | 74.37±0.39 | 70.87±0.99 | 74.68±0.05 | 75.67±0.22 | 76.89±0.25 | 76.98 |
DenseNet-40-12 | 73.06±0.31 | 71.45±0.34 | 71.60±0.38 | 71.25±0.35 | 71.23±0.14 | 72.52±0.42 | 73.09±0.16 | 73.11 |
WRN-20-8 | 79.77±0.07 | 79.40±0.12 | 79.10±0.39 | 78.22±0.14 | 78.83±0.06 | 79.37±0.30 | 80.51±0.49 | 80.58 |
Network | DML | CL | ONE | FFL-S | OKDDip | KDCL | PCL | ours |
---|---|---|---|---|---|---|---|---|
ResNet-32 | 93.94±0.07 | 94.02±0.28 | 94.20±0.12 | 94.01±0.11 | 94.17±0.15 | 94.01±0.08 | 94.33±0.12 | 94.35 |
ResNet-110 | 94.53±0.25 | 95.19±0.11 | 95.16±0.30 | 94.72±0.06 | 95.14±0.10 | 95.11±0.16 | 95.53±0.16 | 95.47 |
VGG-16 | 94.13±0.07 | 94.14±0.15 | 94.14±0.23 | 93.22±0.08 | 93.98±0.06 | 94.09±0.12 | 94.74±0.02 | 93.87 |
DenseNet-40-12 | 93.59±0.26 | 93.05±0.25 | 93.08±0.21 | 93.28±0.16 | 92.64±0.22 | 93.87±0.08 | 94.13±0.13 | 93.69 |
WRN-20-8 | 95.20±0.13 | 94.59±0.08 | 94.70±0.14 | 94.72±0.13 | 94.83±0.15 | 95.27±0.16 | 95.42±0.04 | 95.53 |
This work is developed based on the following works:
CuriousAI/mean-teacher: A state-of-the-art semi-supervised method for image recognition (github.com)
If you find this work useful, please give us a star, thanks :)