2 citations · 2 across the 8 of their papers we have counts for
6 papers · 1 filter
PixelUMM: Encoder-Free Unified Image and Video Understanding and Generation
Cong Wei, Xuanchi Ren, Bryan Chu +8
Unified Multimodal Models (UMMs) often rely on separate visual representations for understanding and generation, increasing visual context length and complicating integration with…
Context-Matched Distillation: Teacher Causality for Autoregressive Video Distillation
Hmrishav Bandyopadhyay, Xuanchi Ren, Zijian Huang +7
Interactive autoregressive video generation demands both low-latency rollouts and precise online control. Few-step distillation accelerates generation by reducing denoising steps,…
NVIDIA OmniDreams: Real-Time Generative World Model for Closed-Loop Autonomous Vehicle Simulation
NVIDIA, :, Aarti Basant +33
As autonomous vehicle capabilities advance, the safe evaluation of driving policies in long-tail scenarios remains a critical bottleneck. In closed-loop simulation, the driving pol…
Cosmos 3: Omnimodal World Models for Physical AI
NVIDIA, :, Aditi +293
We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences within a unified mixture-of-t…
PiD: Fast and High-Resolution Latent Decoding with Pixel Diffusion
Yifan Lu, Qi Wu, Jay Zhangjie Wu +4
Most practical high-resolution text-to-image systems, including latent diffusion and autoregressive models, perform generation in a compact latent space, and a decoder maps the gen…
ArtiFixer: Enhancing and Extending 3D Reconstruction with Auto-Regressive Diffusion Models
Riccardo de Lutio, Tobias Fischer, Yen-Yu Chang +7
Per-scene optimization methods such as 3D Gaussian Splatting provide state-of-the-art novel view synthesis quality but extrapolate poorly to under-observed areas. Methods that leve…