NVIDIA’s AI Learned From 5,000 Human Moves!

❤️ Check out Lambda here and sign up for their GPU Cloud: https://lambdalabs.com/paper

???? The papers are available here:
Consistory: Training-Free Consistent Text-to-Image Generation
https://research.nvidia.com/labs/par/consistory/

SuperPADL: Scaling Language-Directed Physics-Based Control with Progressive Supervised Distillation
https://research.nvidia.com/publication/2024-07_superpadl-scaling-language-directed-physics-based-control-progressive

Simplicits: Mesh-Free, Geometry-Agnostic, Elastic Simulation
https://research.nvidia.com/labs/toronto-ai/simplicits/

Walkin' Robin: Walk on Stars with Robin Boundary Conditions
https://research.nvidia.com/labs/prl/publication/miller2024wost/
(more media here: https://blogs.nvidia.com/blog/siggraph-2024-ai-graphics-research/ )

A Free-Space Diffraction BSDF
https://research.nvidia.com/labs/rtr/publication/steinberg2024diffraction/

Surface-Filling Curve Flows via Implicit Medial Axes
https://www.dgp.toronto.edu/projects/surface-filling-curves/

???? My paper on simulations that look almost like reality is available for free here:
https://rdcu.be/cWPfD

Or this is the orig. Nature Physics link with clickable citations:
https://www.nature.com/articles/s41567-022-01788-5

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