Auto-captions on GIF: A Large-scale Video-sentence Dataset for Vision-language Pre-training

• URL: http://arxiv.org/abs/2007.02375v1
• Date: Sun, 5 Jul 2020 16:11:57 GMT
• Title: Auto-captions on GIF: A Large-scale Video-sentence Dataset for Vision-language Pre-training
• Authors: Yingwei Pan and Yehao Li and Jianjie Luo and Jun Xu and Ting Yao and Tao Mei
• Abstract summary: Auto-captions on GIF dataset is a new large-scale pre-training dataset for generic video understanding. All video-sentence pairs are created by automatically extracting and filtering video caption annotations from billions of web pages.
• Score: 112.91603911837436
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this work, we present Auto-captions on GIF, which is a new large-scale pre-training dataset for generic video understanding. All video-sentence pairs are created by automatically extracting and filtering video caption annotations from billions of web pages. Auto-captions on GIF dataset can be utilized to pre-train the generic feature representation or encoder-decoder structure for video captioning, and other downstream tasks (e.g., sentence localization in videos, video question answering, etc.) as well. We present a detailed analysis of Auto-captions on GIF dataset in comparison to existing video-sentence datasets. We also provide an evaluation of a Transformer-based encoder-decoder structure for vision-language pre-training, which is further adapted to video captioning downstream task and yields the compelling generalizability on MSR-VTT. The dataset is available at \url{http://www.auto-video-captions.top/2020/dataset}.

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