Awesome
Learning_to_diversify
This is the official code repository for ICCV2021 'Learning to Diversify for Single Domain Generalization'.
Paper Link: http://arxiv.org/abs/2108.11726
Update: Single DG with Resnet-18
Recently, we receive increasing enquiry about single DG on PACS with Resnet-18 Backbone. (In the paper, we reported Alexnet result) Please try hyperparameters lr=0.002 and e=50, to start your experiment.
We report the following single DG result on PACS, with resnet-18 as the backbone network:
| Src. domain | P | A | C | S | avg. |
|---|---|---|---|---|---|
| Avg. Tar. Acc. | 52.29 | 76.91 | 77.88 | 53.66 | 65.18 |
Quick start: (Generalizing from art, cartoon, sketch to photo domain with ResNet-18)
- Install the required packages.
- Download PACS dataset.
- Execute the following code.
bash run_main_PACS.sh
Change dataset
In line 266-300 of train.py, we provide 3 different datasets settings (PACS, VLCS, OFFICE-HOME). You can simply uncomment it to start your own experiment. It may require hyper-parameter fine tuning for some of the tasks.