For the evaluation in the downstream task of video captioning, we will use and publish in a leaderboard the automatic metric results, including BLEU@4, METEOR, CIDEr and SPICE, on the testing set of MSR-VTT dataset.

For the evaluation in the downstream task of video categorization, we will report the top-1 accuracy on the testing set of Downstream dataset.

@article{autogif2020,
title={Auto-captions on GIF: A Large-scale Video-sentence Dataset for Vision-language Pre-training},
author={Yingwei Pan and Yehao Li and Jianjie Luo and Jun Xu and Ting Yao and Tao Mei},
journal={arXiv preprint arXiv:2007.02375},
year={2020}}
                                    
@inproceedings{msrvtt,
title={MSR-VTT: A Large Video Description Dataset for Bridging Video and Language},
author={Jun Xu and Tao Mei and Ting Yao and Yong Rui},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2016}}