CLC number: TP181
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2023-10-17
Cited: 0
Clicked: 1770
Citations: Bibtex RefMan EndNote GB/T7714
Yiming LEI, Jingqi LI, Zilong LI, Yuan CAO, Hongming SHAN. Prompt learning in computer vision: a survey[J]. Frontiers of Information Technology & Electronic Engineering, 2024, 25(1): 42-63.
@article{title="Prompt learning in computer vision: a survey",
author="Yiming LEI, Jingqi LI, Zilong LI, Yuan CAO, Hongming SHAN",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="25",
number="1",
pages="42-63",
year="2024",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2300389"
}
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%T Prompt learning in computer vision: a survey
%A Yiming LEI
%A Jingqi LI
%A Zilong LI
%A Yuan CAO
%A Hongming SHAN
%J Frontiers of Information Technology & Electronic Engineering
%V 25
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%P 42-63
%@ 2095-9184
%D 2024
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2300389
TY - JOUR
T1 - Prompt learning in computer vision: a survey
A1 - Yiming LEI
A1 - Jingqi LI
A1 - Zilong LI
A1 - Yuan CAO
A1 - Hongming SHAN
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 25
IS - 1
SP - 42
EP - 63
%@ 2095-9184
Y1 - 2024
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2300389
Abstract: prompt learning has attracted broad attention in computer vision since the large pre-trained vision-language models (VLMs) exploded. Based on the close relationship between vision and language information built by VLM, prompt learning becomes a crucial technique in many important applications such as artificial intelligence generated content (AIGC). In this survey, we provide a progressive and comprehensive review of visual prompt learning as related to AIGC. We begin by introducing VLM, the foundation of visual prompt learning. Then, we review the vision prompt learning methods and prompt-guided generative models, and discuss how to improve the efficiency of adapting AIGC models to specific downstream tasks. Finally, we provide some promising research directions concerning prompt learning.
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