Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and
  Language Models
Authors: name: Muhammad Maaz; name: Hanoona Rasheed; name: Salman Khan; name: Fahad Shahbaz Khan
Published: 2023-06-08 17:59:56

Abstract: Conversation agents fueled by Large Language Models (LLMs) are providing a
new way to interact with visual data. While there have been initial attempts
for image-based conversation models, this work addresses the underexplored
field of video-based conversation by introducing Video-ChatGPT. It is a
multimodal model that merges a video-adapted visual encoder with a LLM. The
model is capable of understanding and generating human-like conversations about
videos. We introduce a new dataset of 100,000 video-instruction pairs used to
train Video-ChatGPT acquired via manual and semi-automated pipeline that is
easily scalable and robust to label noise. We also develop a quantiative
evaluation framework for video-based dialogue models to objectively analyse the
strengths and weaknesses of proposed models. Our code, models, instruction-sets
and demo are released at https://github.com/mbzuai-oryx/Video-ChatGPT.