VLM_survey

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VLM_survey is an Open Source research and education tool that provides a systematic survey of Vision-Language Models (VLMs) for various visual recognition tasks. It includes a comprehensive collection of papers, datasets, and methods related to VLMs.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is VLM_survey?

VLM_survey is an open-source repository offering a systematic survey of Vision-Language Models (VLMs) applied to diverse visual recognition tasks such as image classification, object detection, and semantic segmentation. It serves as a valuable resource for researchers, providing an extensive collection of academic papers, widely adopted datasets for VLM pre-training and evaluation, and categorized methodologies for VLM pre-training, transfer learning, and knowledge distillation. The repository also highlights recent advancements and future research directions in the field, making it an essential reference for anyone working with or studying VLMs.

Best used for

Ideal for professors and researchers who need to conduct comprehensive literature reviews on Vision-Language Models, identify relevant datasets for their studies, and understand the latest pre-training, transfer learning, and knowledge distillation methods. Especially valuable for academic research and staying updated on VLM advancements.

Common actions

survey vision-language models

explore VLM research

find VLM datasets

categorize VLM methods

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Capabilities

Key features

VLM paper collection
VLM pre-training methods
VLM transfer learning methods
VLM knowledge distillation
VLM datasets list

Target Audience

professor

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

How can I contribute to the VLM_survey repository?

You can contribute by forking the project, adding new papers with their title, link, conference, and project/code link to the README.md, and then submitting a pull request to the main branch. You can also open an issue if you find missing papers.

What types of visual recognition tasks are covered in the survey?

The survey covers a wide range of visual recognition tasks, including image classification, object detection, semantic segmentation, and other vision tasks where Vision-Language Models are applied and investigated.

Does the VLM_survey include information on datasets?

Yes, the VLM_survey provides comprehensive lists of widely adopted datasets for both VLM pre-training and VLM evaluation, detailing their year, number of image-text pairs, language, and evaluation metrics.

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Study Assistants Knowledge Management Course Creation Scientific Computing Summarization Language Learning

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