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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
(TPAMI 2024) A Survey on Open Vocabulary Learning
| Date | Stars |
|---|---|
| 2026-07-24 | 998 |
| 2026-07-25 | 998 |
| 2026-07-28 | 999 |
| 2026-07-30 | 999 |
| 2026-08-06 | 999 |
Today
— stars today
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Momentum
0.0
growth rate 0.00%/day
[](https://github.com/sindresorhus/awesome)
[](https://github.com/jianzongwu/Awesome-Open-Vocabulary/pulls)
<br />
<p align="center">
<h1 align="center">Towards Open Vocabulary Learning: A Survey</h1>
<p align="center">
<b> T-PAMI, 2024 </b>
<br />
<a href="https://jianzongwu.github.io/"><strong>Jianzong Wu <sup>*</sup></strong></a>
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<a href="https://lxtgh.github.io/"><strong> Xiangtai Li <sup>*</sup> </strong></a>
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<a href="https://xushilin1.github.io/"><strong>Shilin Xu <sup>*</sup></strong></a>
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<a href="https://yuanhaobo.me/"><strong>Haobo Yuan <sup>*</sup></strong></a>
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<a href="https://henghuiding.github.io/"><strong>Henghui Ding</strong></a>
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<a href="https://iboing.github.io/"><strong>Yibo Yang</strong></a>
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<a href="https://xialipku.github.io/"><strong>Xia Li</strong></a>
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<a href="https://zhangzjn.github.io/"><strong>Jiangning Zhang</strong></a>
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<a href="https://scholar.google.com/citations?user=T4gqdPkAAAAJ&hl=zh-CN"><strong>Yunhai Tong</strong></a>
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<a href="http://scholar.google.com/citations?user=IL3mSioAAAAJ&hl=zh-CN"><strong>Xudong Jiang</strong></a>
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<a href="https://scholar.google.com/citations?user=rVsGTeEAAAAJ&hl=zh-CN"><strong>Bernard Ghanem</strong></a>
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<a href="https://scholar.google.com/citations?user=RwlJNLcAAAAJ&hl=zh-CN"><strong>Dacheng Tao</strong></a>
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</p>
<p align="center">
<a href='https://arxiv.org/abs/2306.15880'>
<img src='https://img.shields.io/badge/arXiv-PDF-green?style=flat&logo=arXiv&logoColor=green' alt='arXiv PDF'>
</a>
<a href='https://ieeexplore.ieee.org/document/10420487'>
<img src='https://img.shields.io/badge/TPAMI-PDF-blue?style=flat&logo=IEEE&logoColor=green' alt='TPAMI PDF'>
</a>
</p>
<br />
This repo is used for recording, tracking, and benchmarking several recent open vocabulary methods to supplement our [survey](https://arxiv.org/abs/2306.15880).
If you find any work missing or have any suggestions (papers, implementations, and other resources), feel free to [pull requests](https://github.com/jianzongwu/Awesome-Open-Vocabulary/pulls).
We will add the missing papers to this repo as soon as possible.
### 🔥Add Your Paper in our Repo and Survey!!!!!
[-] You are welcome to give us an issue or PR for your open vocabulary learning work !!!!!
[-] Note that: Due to the huge paper in Arxiv, we are sorry to cover all in our survey. You can directly present a PR into this repo and we will record it for next version update of our survey.
[-] **Our survey will be updated in 2024.3.**
### 🔥New
[-] Our work is accepted by T-PAMI !!! 🔥🔥🔥
[-] We update GitHub to record the available paper by the end of **2024/1/10**.
[-] We update GitHub to record the available paper by the end of **2023/7/20**.
### 🔥Highlight!!
[1] The first survey for open vocabulary learning, including open vocabulary detection/segmentation/tracking.
[2] It also contains several related domains, including foundation model tuning and open-world detection.
[3] We list detailed results for the most representative works and give a fairer and clearer comparison of different approaches.
## Introduction
This survey presents the first detailed survey on open vocabulary tasks, including open-vocabulary object detection, open-vocabulary segmentation, and 3D/video open-vocabulary tasks.
## Summary of Contents
- [Introduction](#introduction)
- [Summary of Contents](#summary-of-contents)
- [Methods: A Survey](#methods-a-survey)
- [Open Vocabulary Object Detection](#open-vocabulary-object-detection)
- [Open Vocabulary Segmentation](#open-vocabulary-segmentation)
- [Semantic Segmentation](#semantic-segmentation)
- [InstancExcerpt of 35,757 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:bad0a381296f6333, topic:computer-vision, readme:object detection, readme:semantic segmentation
matched fp:bad0a381296f6333, topic:deep-learning
