# Computer-Vision-in-the-Wild/CVinW_Readings

A collection of papers on the topic of ``Computer Vision in the Wild (CVinW)''

Repository: https://github.com/Computer-Vision-in-the-Wild/CVinW_Readings
Canonical: https://ross.abutalabs.com/products/cvinw_readings
License Family: other
Last push: 2024-03-14T18:59:10+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1435, "days_push": 902, "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 1373, forks 57 (observed 2026-08-28T04:04:32.912163+00:00)

## What it is
An awesome-style curated collection of research papers on Computer Vision in the Wild (CVinW), covering task-level transfer with pre-trained vision models, efficient model adaptation, and out-of-domain generalization. It serves as a reading list and community-maintained resource for researchers studying transferable visual foundation models.

## Use cases
- find papers on computer vision in the wild
- research reading list for vision foundation models
- learn about task transfer with pre-trained vision models
- find papers on parameter-efficient model adaptation
- study out-of-domain generalization in computer vision
- find benchmarks for visual recognition transfer

## When to choose
- you are researching transferable vision foundation models and want a curated paper list
- you need references on efficient adaptation or domain generalization for vision models

## When to avoid
- you need runnable code or a software library rather than a paper collection
- you need tutorials for beginners rather than research papers

## Facets
- artifact type: learning-resource
- maturity: active
- function: computer-vision, machine-learning
- domain: computer-vision, machine-learning, deep-learning, tutorials
- platform: cross-platform
- tags: awesome-list, papers, computer-vision-in-the-wild, transfer-learning, research-collection, foundation-models

## Member repositories
- Computer-Vision-in-the-Wild/CVinW_Readings (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:32.912163+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 2026-08-30T04:40:39.721770+00:00, confidence not recorded.
  - readme: https://github.com/Computer-Vision-in-the-Wild/CVinW_Readings (fetched 2026-08-28T04:04:32.912163+00:00, sha 4fcb92abccd8)
- Data as of 2026-08-30T08:39:29.467469+00:00.