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This is the official PyTorch implementation of our paper: Adversarial Bipartite Graph Learning for Video Domain Adaptation

• Python 3.7, PyTorch 1.2, CUDA 10.2

Experiments are conducted on four datasets: UCF-HMDB_small, UCF-HMDB_full, UCF-Olympic, Kinetics-Gamplay.

The downloaded files need to store in ./dataset.

Pre-extracted features and data lists can be downloaded as,

• Features

  • UCF: download
  • HMDB: download
  • Olympic: training | validation

• Data lists

  • UCF-Olympic
    • UCF: training list | validation list
    • Olympic: training list | validation list
  • UCF-HMDB_small
    • UCF: training list | validation list
    • HMDB: training list | validation list
  • UCF-HMDB_full
    • UCF: training list | validation list
    • HMDB: training list | validation list

• Kinetics-Gameplay: please fill this form to request the features and data lists.
  The Kinetics-Gameplay dataset is licensed under CC BY-NC-SA 4.0 for non-commercial purposes only.

• training/validation: Run ./script_<DATASET_NAME>_G.sh E.g., script_HMDB_Ucf_G.sh