# jianzongwu/Awesome-Open-Vocabulary

(TPAMI 2024) A Survey on Open Vocabulary Learning

Repository: https://github.com/jianzongwu/Awesome-Open-Vocabulary
Canonical: https://ross.abutalabs.com/products/awesome-open-vocabulary
Homepage: https://arxiv.org/abs/2306.15880
License Family: other
Topics: computer-vision, deep-learning, open-vocabulary, tpami-2024
Last push: 2026-05-12T06:41:25+00:00

## Health v2 (maintenance only)
Score: 66/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 82, release rhythm 35, longevity 84
- inputs: {"age_days": 1183, "days_push": 113, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1003, forks 43 (observed 2026-09-03T02:15:13.153168+00:00)

## What it is
An awesome-list repository accompanying the TPAMI 2024 survey 'Towards Open Vocabulary Learning: A Survey'. It records, tracks, and benchmarks recent open-vocabulary learning methods for detection and segmentation, with community contributions via pull requests.

## Use cases
- find papers on open vocabulary detection and segmentation
- survey open vocabulary learning methods
- track new open-vocabulary research papers
- compare open vocabulary benchmarks
- learn the difference between open vocabulary, zero-shot, and open-set recognition
- find vision-language pretraining resources for visual scene understanding

## When to choose
- you are researching open vocabulary learning and want a curated, updated paper list
- you need a structured overview of open-vocabulary detection and segmentation methods
- you want to benchmark or compare recent open vocabulary approaches

## When to avoid
- you need runnable code or a library rather than a paper list
- you are looking for a maintained software tool with a license
- your topic is unrelated to open vocabulary computer vision

## Facets
- artifact type: learning-resource
- maturity: active
- function: computer-vision, machine-learning, documentation
- domain: computer-vision, deep-learning, awesome-lists, tutorials
- platform: -
- tags: awesome-list, open-vocabulary, survey, tpami, vision-language, paper-tracking, benchmarking, web-server

## Member repositories
- jianzongwu/Awesome-Open-Vocabulary (main) score 66

## Provenance
- Observed fields: from GitHub, fetched 2026-09-03T02:15:13.153168+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:14:00.806031+00:00, confidence not recorded.
  - readme: https://github.com/jianzongwu/Awesome-Open-Vocabulary (fetched 2026-09-03T02:15:13.153168+00:00, sha af45be1e8adf)
  - homepage: https://arxiv.org/abs/2306.15880 (fetched 2026-08-29T13:14:19.989478+00:00, sha f7d875742714)
  - site_page: https://info.arxiv.org/about/donate.html (fetched 2026-08-29T13:14:19.999411+00:00, sha cca9c3a11c56)
  - site_page: https://info.arxiv.org/about/ourmembers.html (fetched 2026-08-29T13:14:20.003289+00:00, sha 47cbc55ff1de)
  - site_page: https://info.arxiv.org/about (fetched 2026-08-29T13:14:20.005555+00:00, sha a1f16f915a9a)
  - site_page: https://info.arxiv.org/labs/index.html (fetched 2026-08-29T13:14:20.001512+00:00, sha b14a8d05a0ec)
- Data as of 2026-08-30T08:39:29.467469+00:00.