A Dataset for Telling the Stories of Social Media Videos
| Autor: | Marcus Rohrbach, Michael Lewis, Spandana Gella |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Multimedia
Computer science 0103 physical sciences 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Social media 02 engineering and technology 010306 general physics computer.software_genre 01 natural sciences computer Bridging (programming) |
| Zdroj: | EMNLP |
| DOI: | 10.18653/v1/d18-1117 |
| Popis: | Video content on social media platforms constitutes a major part of the communication between people, as it allows everyone to share their stories. However, if someone is unable to consume video, either due to a disability or network bandwidth, this severely limits their participation and communication. Automatically telling the stories using multi-sentence descriptions of videos would allow bridging this gap. To learn and evaluate such models, we introduce VideoStory a new large-scale dataset for video description as a new challenge for multi-sentence video description. Our VideoStory captions dataset is complementary to prior work and contains 20k videos posted publicly on a social media platform amounting to 396 hours of video with 123k sentences, temporally aligned to the video. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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