Review of large vision models and visual prompt engineering

• DOI: 10.1016/j.metrad.2023.100047
• Publication Date: 2023-12-21T02:42:16Z
• Authors: Jiaqi Wang; Zhengliang Liu; Lin Zhao; Zihao Wu; Chong Ma; Sigang Yu; Haixing Dai; Qiushi Yang; Yiheng Liu; Songyao Zhang; Enze Shi; Yi Pan; Tuo Zhang; Dajiang Zhu; Xiang Li; Xi Jiang; Bao Ge; Yixuan Yuan; Dinggang Shen; Tianming Liu; Shu Zhang
• Keywords: FOS: Computer and information sciences; Visual prompt; Vision models; Computer Science - Artificial Intelligence; Computer Vision and Pattern Recognition (cs.CV); R895-920; Computer Science - Computer Vision and Pattern Recognition; Artificial general intelligence; Medical physics. Medical radiology. Nuclear medicine; 03 medical and health sciences; Artificial Intelligence (cs.AI); 0302 clinical medicine

Visual prompt engineering is a fundamental methodology in the field of visual and image artificial general intelligence. As development large vision models progresses, importance becomes increasingly evident. Designing suitable prompts for specific tasks has emerged as meaningful research direction. This review aims to summarize methods employed computer domain engineering, exploring latest advancements engineering. We present influential range on these models. It our hope that this provides comprehensive systematic description based models, offering valuable insights future researchers their exploration field.