What is it about?
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
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Why is it important?
Fine-tuning techniques become a hype in the era of large multimodal foundation models. Readers will quickly grasp the recent advances in fine-tuning from aspects such as theory, techniques, and future works.
Perspectives
Computer vision is almost everywhere in different domains, and this work outlook the recent hype of fine-tuning and future human-machine interactions, laymen or experts in computer vision are all recommended to go through this easy-to-read article.
Bruce X.B. Yu
Zhejiang University
Read the Original
This page is a summary of: Visual Tuning, ACM Computing Surveys, July 2024, ACM (Association for Computing Machinery),
DOI: 10.1145/3657632.
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