This repository is modified from ACAR-Net.

Some key dependencies are listed below, while others are given in requirements.txt.

• Python >= 3.6
• PyTorch >= 1.3, and a corresponding version of torchvision
• ffmpeg (used in data preparation)
• Download pre-trained models, which are listed in pretrained/README.md, to the pretrained folder.
• Prepare data. Please refer to DATA.md.

Default values for arguments nproc_per_node, backend and master_port are 4, gloo and 31114 respectively.

python main.py --config CONFIG_FILE [--nproc_per_node N_PROCESSES] [--backend BACKEND] [--master_addr MASTER_ADDR] [--master_port MASTER_PORT]

In this case, the master_addr argument must be provided. Moreover, arguments nnodes and node_rank can be additionally specified (similar to torch.distributed.launch), otherwise the program will try to obtain their values from environment variables. See distributed_utils.py for details.

Please cite with the following Bibtex code:

@inproceedings{zhao2023open,
  title={Open Set Action Recognition via Multi-Label Evidential Learning},
  author={Zhao, Chen and Du, Dawei and Hoogs, Anthony and Funk, Christopher},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2023}
}

Or

Zhao, Chen, Du, Dawei, Hoogs, Anthony and Funk, Christopher. "Open Set Action Recognition via Multi-Label Evidential Learning." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2023.