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ROS (Rotation-based Open Set)

PyTorch official implementation of "On the Effectiveness of Image Rotation for Open Set Domain Adaptation" in European Conference on Computer Vision 2020, ECCV2020

Test Image 1

Experiments

In order to replicate the results shown in the paper (Tables 1,2) please follow these instructions:

  1. Download Office-31 and Office-Home datasets:

  2. Use the python version: Python 3.6.8

    Install all the libreries requested with the command:

    pip3 install -r requirements_ROS.txt

    Please note that, for the sake of convenience, we also provide a Dockerfile to directly create a docker container with all the necessary requirements.

  3. Go into the folder ROS and:

    3a. In order to replicate the experiments of Office31 dataset with ResNet-50 (Table 1) run:

     train_resnet50_office31.sh replacing 
     "/.../" with "/path_in_which_you_save_ROS/"
    

    3b. In order to replicate the experiments of Office-Home dataset with ResNet-50 (in Table 2) run:

     train_resnet50_officehome.sh replacing 
     "/.../" with "/path_in_which_you_save_ROS/"        
     
    

    3c. In order to replicate the experiments of Office31 dataset with VggNet (in Table 1) run:

     train_vgg_office31.sh replacing 
     "/.../" with "/path_in_which_you_save_ROS/"
    

You can also replicate the results obtained for STA_max,STA_sum,OSBP and UAN (Tables 1,2) following the instructions of the GitHub repositories proposed by the authors:

Citation

To cite, please use the following reference:

@inproceedings{BucciLoghmaniTommasi2020,
  title={On the Effectiveness of Image Rotation for Open Set Domain Adaptation},
  author={Silvia Bucci, Mohammad Reza Loghmani, Tatiana Tommasi},
  booktitle={European Conference on Computer Vision (ECCV)},
  year={2020}
}