11 citations · 15 across the 9 of their papers we have counts for
5 papers · 1 filter
World Simulation with Video Foundation Models for Physical AI
NVIDIA, :, Arslan Ali +87
We introduce [Cosmos-Predict2.5], the latest generation of the Cosmos World Foundation Models for Physical AI. Built on a flow-based architecture, [Cosmos-Predict2.5] unifies Text2…
ViPE: Video Pose Engine for 3D Geometric Perception
Jiahui Huang, Qunjie Zhou, Hesam Rabeti +12
Accurate 3D geometric perception is an important prerequisite for a wide range of spatial AI systems. While state-of-the-art methods depend on large-scale training data, acquiring…
Scenethesis: A Language and Vision Agentic Framework for 3D Scene Generation
Lu Ling, Chen-Hsuan Lin, Tsung-Yi Lin +7
Synthesizing interactive 3D scenes from text is essential for gaming, virtual reality, and embodied AI. However, existing methods face several challenges. Learning-based approaches…
Dynamic Camera Poses and Where to Find Them
Chris Rockwell, Joseph Tung, Tsung-Yi Lin +3
Annotating camera poses on dynamic Internet videos at scale is critical for advancing fields like realistic video generation and simulation. However, collecting such a dataset is d…
Cosmos World Foundation Model Platform for Physical AI
NVIDIA, :, Niket Agarwal +76
Physical AI needs to be trained digitally first. It needs a digital twin of itself, the policy model, and a digital twin of the world, the world model. In this paper, we present th…