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

Author: Two Minute Papers - Bewertung: 110x - Views:1396

❤️ 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

🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible:
Alex Balfanz, Alex Haro, B Shang, Benji Rabhan, Gaston Ingaramo, Gordon Child, John Le, Kyle Davis, Loyal Alchemist, Lukas Biewald, Martin, Michael Albrecht, Michael Tedder, Owen Skarpness, Richard Sundvall, Taras Bobrovytsky, Ted Johnson, Thomas Krcmar, Tybie Fitzhugh, Ueli Gallizzi.
If you wish to appear here or pick up other perks, click here: https://www.patreon.com/TwoMinutePapers

My research: https://cg.tuwien.ac.at/~zsolnai/
X/Twitter: https://twitter.com/twominutepapers
Thumbnail design: Felícia Zsolnai-Fehér - http://felicia.hu

#NVIDIA