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Data drives progress in computer vision. We introduce Infinigen: a generator of unlimited high-quality 3D data. 100% procedural, no external assets, no AI. Free and open source. Intro video: youtu.be/6tgspeI-GHY Code: github.com/princeton-vl/i… CVPR23: Wed 4:30PM, Poster 27

Infinigen v1.0.1 is out, with license switched to BSD, line credits, expanded docs for ground truth, and miscellaneous fixes. Please do a fresh git clone if possible as we have reset the commit history to show line credits (sorry for any inconvenience from this one-off reset).

A roadmap page for Infinigen is now up (short term for now) infinigen.org/roadmap Find out what is coming up and send us requests to help us prioritize!

Infinigen v1.0.3 is released! github.com/princeton-vl/i… You can now generate water and fire: github.com/princeton-vl/i… Also check out how to implement your own assets with python: github.com/princeton-vl/i…

Infinigen v1.1.1 is out: updated to Blender3.6 and revamped installation to be more robust. See github.com/princeton-vl/i… for more, including our "minimal" install variant which lets you generate non-terrain assets in almost any python environment (no local compilation required).

How good is the compositional generation capability of current Text-to-Image models? arxiv.org/abs/2408.14339 Introducing ConceptMix, our new benchmark that evaluates how well models can generate images that accurately combine multiple visual concepts, pushing beyond simple,

Princeton365: A Diverse Dataset with Accurate Camera Pose Karhan Kayan, Stamatis Alexandropoulos, Rishabh Jain, Yiming Zuo, Erich Liang, Jia Deng tl;dr: dataset with gt camera pose and 6 DoF camera motion; new optical-flow based metric arxiv.org/abs/2506.09035