@inproceedings {28211,
	title = {Reproducibility Companion Paper: Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework},
	journal = {Proceedings of the 29th ACM International Conference on Multimedia (MM {\textquoteright}21)},
	year = {2021},
	pages = {3630{\textendash}3632},
	publisher = {ACM},
	address = {New York, NY, USA},
	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.},
	isbn = {9781450386517},
	doi = {10.1145/347408510.1145/3474085.3477939},
	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},
	author = {Heng Tao {Shen} and Zhuang, Yueting and John R. {Smith} and Yang, Yang and Cesar, Pablo and Metze, Florian and Prabhakaran, Balakrishnan and Tao, Li and Wang, Xueting and Yamasaki, Toshihiko and Chen, Jingjing and Hicks, Steven}
}
