12 citations · 34 across the 12 of their papers we have counts for
6 papers · 1 filter
SAGE: Scalable Agentic 3D Scene Generation for Embodied AI
Hongchi Xia, Xuan Li, Zhaoshuo Li +9
Real-world data collection for embodied agents remains costly and unsafe, calling for scalable, realistic, and simulator-ready 3D environments. However, existing scene-generation s…
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…
Cosmos-Transfer1: Conditional World Generation with Adaptive Multimodal Control
NVIDIA, :, Hassan Abu Alhaija +38
We introduce Cosmos-Transfer, a conditional world generation model that can generate world simulations based on multiple spatial control inputs of various modalities such as segmen…
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…
Edify 3D: Scalable High-Quality 3D Asset Generation
NVIDIA, :, Maciej Bala +22
We introduce Edify 3D, an advanced solution designed for high-quality 3D asset generation. Our method first synthesizes RGB and surface normal images of the described object at mul…
BEHAVIOR Vision Suite: Customizable Dataset Generation via Simulation
Yunhao Ge, Yihe Tang, Jiashu Xu +20
The systematic evaluation and understanding of computer vision models under varying conditions require large amounts of data with comprehensive and customized labels, which real-wo…