RESEARCH

NLP

A Dataset for Telling the Stories of Social Media Videos

October 31, 2018

Abstract

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 sourced 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.

Download the Paper

AUTHORS

Written by

Marcus Rohrbach

Mike Lewis

Spandana Gella

Publisher

EMNLP

Related Publications

July 23, 2024

HUMAN & MACHINE INTELLIGENCE

CONVERSATIONAL AI

The Llama 3 Herd of Models

Llama team

July 23, 2024

June 25, 2024

NLP

Neurons in Large Language Models: Dead, N-gram, Positional

Elena Voita, Javier Ferrando Monsonis, Christoforos Nalmpantis

June 25, 2024

June 25, 2024

SPEECH & AUDIO

NLP

Textless Acoustic Model with Self-Supervised Distillation for Noise-Robust Expressive Speech-to-Speech Translation

Min-Jae Hwang, Ilia Kulikov, Benjamin Peloquin, Hongyu Gong, Peng-Jen Chen, Ann Lee

June 25, 2024

June 14, 2024

NLP

How to Train Your DRAGON: Diverse Augmentation Towards Generalizable Dense Retrieval

Sheng-Chieh Lin, Akari Asai, Minghan Li, Barlas Oguz, Jimmy Lin, Scott Yih, Xilun Chen

June 14, 2024

Help Us Pioneer The Future of AI

We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.