Vlm Survey: Find vision-language model research

Understand the project

Practical overview

Use it when beginning or extending a literature search on vision-language models for image classification, object detection or semantic segmentation.

Researchers surveying vision-language methods across visual recognition tasks.
Students seeking papers and project links on classification, detection or segmentation.
Contributors who want to propose related papers for the collection.

Find a survey paper on vision-language models for visual recognition.
Browse research entries by their paper, venue and associated project or code links.
Propose a related paper using the repository's stated contribution process.

Before you choose

The collection is hosted in a public GitHub repository.

The repository is a survey and research index; it does not provide model weights, an API or an executable inference tool.
Entries use a consistent paper, venue and project/code link format, making the collection useful for tracing individual studies.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Prepare and submit a repository contribution for a related paper.

Fork the project into your own repository.
Add the paper to README.md using the listed title, paper link, conference, and project/code link format.
Submit a pull request to the repository branch.

A pull request proposing the paper for inclusion in the collection.

The repository describes the contribution process but does not guarantee that a proposed entry will be accepted.

Evidence and transparency

Source record details

Source availability: Active
Sources checked: 3 November 2026
Original website title: jingyi0000/VLM_survey · Official homepage title · retained in its source language