Review of Large Vision Models and Visual Prompt Engineering
Abstract
Visual prompt engineering is a fundamental technology in the field of visual and image Artificial General Intelligence, serving as a key component for achieving zero-shot capabilities. As the development of large vision models progresses, the importance of prompt engineering becomes increasingly evident. Designing suitable prompts for specific visual tasks has emerged as a meaningful research direction. This review aims to summarize the methods employed in the computer vision domain for large vision models and visual prompt engineering, exploring the latest advancements in visual prompt engineering. We present influential large models in the visual domain and a range of prompt engineering methods employed on these models. It is our hope that this review provides a comprehensive and systematic description of prompt engineering methods based on large visual models, offering valuable insights for future researchers in their exploration of this field.
Keywords
Cite
@article{arxiv.2307.00855,
title = {Review of Large Vision Models and Visual Prompt Engineering},
author = {Jiaqi Wang and Zhengliang Liu and Lin Zhao and Zihao Wu and Chong Ma and Sigang Yu and Haixing Dai and Qiushi Yang and Yiheng Liu and Songyao Zhang and Enze Shi and Yi Pan and Tuo Zhang and Dajiang Zhu and Xiang Li and Xi Jiang and Bao Ge and Yixuan Yuan and Dinggang Shen and Tianming Liu and Shu Zhang},
journal= {arXiv preprint arXiv:2307.00855},
year = {2023}
}