@misc{16321,
  author = {Heng Shen and Yueting Zhuang and John Smith and Yang Yang and Pablo Cesar and Florian Metze and Balakrishnan Prabhakaran and Li Tao and Xueting Wang and Toshihiko Yamasaki and Jingjing Chen and Steven Hicks},
  title = {Reproducibility Companion Paper: Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework},
  abstract = {In this companion paper, we provide details of the artifacts to support the replication of "Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework", which was presented at MM{\textquoteright}20. The Inter-intra Contrastive (IIC) framework aims to extract more discriminative temporal information by extending intra-negative samples in contrastive self-supervised learning. In this paper, we first summarize our contribution. Then we explain the file structure of the source code and detailed settings. Since our proposal is a framework which contain a lot of different settings, we provide some custom settings to help other researchers to use our methods easily. The source code is available at https://github.com/BestJuly/IIC.},
  year = {2021},
  journal = {Proceedings of the 29th ACM International Conference on Multimedia (MM {\textquoteright}21)},
  pages = {3630{\textendash}3632},
  publisher = {ACM},
  address = {New York, NY, USA},
  isbn = {9781450386517},
  url = {https://dl.acm.org/doi/proceedings/10.1145/3474085https://dl.acm.org/doi/10.1145/3474085.3477939https://dl.acm.org/doi/pdf/10.1145/3474085.3477939},
  doi = {10.1145/347408510.1145/3474085.3477939},
}