Fine-tuning visual models has been widely shown promising performance on many downstream visual tasks. With the surprising development of pre-trained visual foundation models, visual tuning jumped out of the standard modus operandi that fine-tunes the whole pre-trained model or just the fully connected layer. Instead, recent advances can achieve superior performance than full-tuning the whole pre-trained parameters by updating far fewer parameters, enabling edge devices and downstream applications to reuse the increasingly large foundation models deployed on the cloud. With the aim of helping researchers get the full picture and future directions of visual tuning, this survey characterizes a large and thoughtful selection of recent works, providing a systematic and comprehensive overview of existing work and models. Specifically, it provides a detailed background of visual tuning and categorizes recent visual tuning techniques into five groups: fine-tuning, prompt tuning, adapter tuning, parameter tuning, and remapping tuning. Meanwhile, it offers some exciting research directions for prospective pre-training and various interactions in visual tuning.

Bruce X.B. Yu

Jianlong Chang

Haixin Wang

Lingbo Liu

Shijie Wang

Zhiyu Wang

Junfan Lin

Lingxi Xie

Haojie Li

Zhouchen Lin

Qi Tian

Chang Wen Chen

ACM Computing Surveys

这些全面、易读的调查和辅导论文提供了文献导览，并向那些寻求以一种易于理解的方式学习其专业以外领域基础知识的人解释主题。计算调查 (CSUR) 中精心策划和介绍的介绍也是研究人员和专业人士发展观点和识别复杂技术趋势的绝佳方式。以新颖有趣的方式将现有和新兴技术（如机器学习）与各种科学和工程领域联系起来的贡献也受到欢迎。

ACM Computing Surveys is a journal that offers comprehensive and accessible survey and tutorial papers. These papers provide literature overviews and explain foundational knowledge in various fields in an easy-to-understand manner, making them ideal for those looking to broaden their expertise. The carefully curated introductions in Computing Surveys (CSUR) help researchers and professionals develop insights and identify complex technological trends. Contributions that connect existing and emerging technologies, such as machine learning, with various scientific and engineering domains in novel and engaging ways are also welcomed.

《ACM Computing Surveys》是一本提供全面、易读的调查和指导论文的期刊。这些论文不仅为读者提供文献导览，还以易于理解的方式解释了各个领域的基础知识，特别适合那些希望拓宽专业知识的人士。计算调查 (CSUR) 中精心策划的介绍部分，帮助研究人员和专业人士发展观点，识别复杂的技术趋势。此外，期刊也欢迎以新颖有趣的方式将现有和新兴技术（如机器学习）与各种科学和工程领域相结合的贡献。

Visual Tuning

This survey characterizes a large and thoughtful selection of recent works, providing a systematic and comprehensive overview of existing work and models, and categorizes recent visual tuning techniques into five groups: fine-tuning, prompt tuning, adapter tuning, parameter tuning, and remapping tuning.

Category	Quartile
计算机科学	1
计算机科学, 计算机理论方法	1

Visual Tuning

ivySCI AI Smartly Parses PDF, Answers Researchers' Questions, and Helps You Understand Papers in Seconds

Journal Info

Category	Quartile
COMPUTER SCIENCE, THEORY & METHODS	1