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Survey of vision-language models for vision tasks

Survey of vision-language models for vision tasks


Vision-Language Models for Vision Tasks: A Survey

arXiv paper abstract https://arxiv.org/abs/2304.00685



Most visual recognition ... rely ... on crowd-labelled data ... and ... train ... for each single visual recognition task, leading to a laborious ... paradigm.


To address the two challenges, Vision-Language Models (VLMs) ... learns ... vision-language correlation from web-scale image-text pairs ... infinitely available on the Internet and enables zero-shot predictions on various visual recognition tasks with a single VLM.


This paper provides a systematic review of visual language models for various visual recognition tasks, including:


(1) the background that introduces the development of visual recognition paradigms;


(2) the foundations of VLM that summarize the widely-adopted network architectures, pre-training objectives, and downstream tasks;


(3) the widely-adopted datasets in VLM pre-training and evaluations;


(4) the review and categorization of existing VLM pre-training methods, VLM transfer

learning methods, and VLM knowledge distillation methods;


(5) the benchmarking, analysis and discussion of the reviewed methods;


(6) several research challenges and potential research directions that could be pursued in the future VLM studies for visual recognition.



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