# extreme-assistant/ICCV2023-Paper-Code-Interpretation

ICCV2021/2019/2017 论文/代码/解读/直播合集，极市团队整理

Repository: https://github.com/extreme-assistant/ICCV2023-Paper-Code-Interpretation
Canonical: https://ross.abutalabs.com/products/iccv2023-paper-code-interpretation
Homepage: https://bbs.cvmart.net
License Family: other
Topics: machine-learning, computer-vision, deep-learning, object-detection, iccv2019, iccv2021, iccv2017, image-classification, image-recognition, image-segmentation, action-recognition
Last push: 2023-09-19T08:24:18+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2711, "days_push": 1079, "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 2295, forks 1361 (observed 2026-08-28T04:06:35.107142+00:00)

## What it is
A curated collection of ICCV conference papers (2017-2023) with links to code, project pages, paper interpretations, and livestream talks, maintained by the ExtremeMart (极市) team. It aggregates accepted paper lists, open-source code spreadsheets, and Chinese-language paper reading summaries.

## Use cases
- find open-source code for ICCV papers
- catch up on ICCV 2023 accepted papers
- read interpretations of computer vision papers
- find best papers from past ICCV conferences
- track paper reading livestreams for CV conferences

## When to choose
- you want a single index of ICCV papers with code and explanations
- you prefer Chinese-language paper summaries and talks
- you're surveying computer vision research across multiple ICCV years

## When to avoid
- you need papers from other venues like CVPR or NeurIPS (separate repos exist)
- you want runnable software rather than a link collection
- you need only English-language resources

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation
- domain: computer-vision, deep-learning, machine-learning, tutorials
- platform: cross-platform
- tags: awesome-list, iccv, conference-papers, paper-interpretation, curated-list

## Member repositories
- extreme-assistant/ICCV2023-Paper-Code-Interpretation (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:35.107142+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 2026-08-30T02:40:20.592915+00:00, confidence not recorded.
  - readme: https://github.com/extreme-assistant/ICCV2023-Paper-Code-Interpretation (fetched 2026-08-28T04:06:35.107142+00:00, sha 5c091408e3a7)
  - homepage: https://bbs.cvmart.net (fetched 2026-08-29T10:21:09.374095+00:00, sha 44bd949212b2)
- Data as of 2026-08-30T08:39:29.467469+00:00.