pwc

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Important caveat: the description states "This repository is no longer maintained," so the lists reflect the state at the time of the last update rather than current research.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.