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zziz/pwc

15,336Audience · researcherComplexity · 1/5Setup · easy

TLDR

A curated, no-longer-maintained index of top machine-learning research papers from major conferences paired with links to their open-source code implementations, sorted by GitHub star count.

Mindmap

mindmap
  root((pwc))
    What it does
      Paper plus code index
      Star-sorted ranking
      Year-grouped lists
    Conferences covered
      CVPR ECCV ICCV
      NeurIPS ICML
    Topics
      Computer vision
      Image generation
      Object detection
    Status
      Archived not maintained
      2013 to 2018 coverage
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Things people build with this

USE CASE 1

Find a working code implementation of a specific ML paper from CVPR, ECCV, NeurIPS, or ICML by browsing the star-sorted list.

USE CASE 2

Discover which computer-vision or ML papers from a given year (2013, 2018) had the most community adoption.

USE CASE 3

Browse top-starred paper implementations to find reproducible research baselines for a new project.

Getting it running

Difficulty · easy Time to first run · 5min

In plain English

This repository is a curated list of academic machine-learning papers paired with their open-source code, sorted by GitHub star count. Each entry in the list shows the paper title, the conference it was published at (such as CVPR, ECCV, ICCV, NIPS, or ICML, all major venues in the machine-learning and computer-vision world), a link to the paper itself, a link to the code that implements it, and the current star count of that code repository. The lists are grouped by year, going back through 2018, 2017, 2016, 2015, 2014, and 2013, with placeholders for older years too. The way it works is purely as a reference index, the repository itself does not contain any of the code, just a long table per year. You scan a year, see what papers existed at top conferences, and click straight through to either the paper PDF or to a GitHub repo where someone has implemented it. The README notes that it was "weekly updated" and that anyone could request a new conference be added to the watchlist via an issue thread. You would use this when you want a quick way to find reproducible machine-learning research with working code, for example, browsing top-cited papers on image generation, object detection, pose estimation, or video synthesis, and being able to immediately jump to a runnable implementation. It is most useful as a discovery tool rather than as software to install. Important caveat: the description states "This repository is no longer maintained," so the lists reflect the state at the time of the last update rather than current research. The full README is longer than what was provided.

Copy-paste prompts

Prompt 1
Based on the papers listed in this repo from 2017, 2018, which object detection methods have open-source implementations I can run today?
Prompt 2
Find me a reproducible GAN implementation from this list that I can fine-tune on my own image dataset.
Prompt 3
Which top-starred papers from CVPR 2018 in this list cover image segmentation, and where is their code?
Prompt 4
Suggest 3 foundational ML papers from this list that a computer vision beginner should implement to build intuition.
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