GPIC: A Giant Permissive Image Corpus for Visual Generation Keshigeyan Chandrasegaran 1 , Kyle Sargent 1 , Suchir Agarwal 1 , Michael Jang 1 , Michael Poli 1,2 , Juan Carlos Niebles 1,4 , Justin Johnson 3 , Jiajun Wu 1 , Li Fei Fei 1 1 Stanford University 2 Radical Numerics 3 University of Michigan 4 Salesforce Research Equal contribution 📄 arXiv 🌎 Website 🤗 Dataset 🤗 Models 🥇 Evaluation toolkit Abstract Studying scalable methods for visual generative modeling requires large, accessible, and stable datasets. We introduce GPIC , a G iant P ermissive I mage C orpus of approximately 28 trillion pixels . GPIC comprises diverse internet images captioned by a state of the art vision language model, including 100M training, 200K validation, and 1M test examples. Moreover, all GPIC images are permissively licensed for both research and commercial use. GPIC is safety filtered, deduplicated, and centrally hosted on Hugging Face. We provide a benchmarking protocol for generative modeling on GPIC. Finally, we provid…
Runs entirely in your browser via DuckDB-Wasm — this dataset's real data file is loaded once, then queried locally. Nothing is sent to a server.
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy