activity
20172026
most citedLearning to Predict 3D Objects with an Interpolation-based Differentiable Renderer

261 citations · 444 across the 32 of their papers we have counts for

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Showing 2025Show all

11 papers · 1 filter

cs.CV2025

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…

cs.CV2025

ChronoEdit: Towards Temporal Reasoning for Image Editing and World Simulation

Jay Zhangjie Wu, Xuanchi Ren, Tianchang Shen +11

Recent advances in large generative models have greatly enhanced both image editing and in-context image generation, yet a critical gap remains in ensuring physical consistency, wh…

cs.CV2025

SANA-Video: Efficient Video Generation with Block Linear Diffusion Transformer

Junsong Chen, Yuyang Zhao, Jincheng Yu +17

We introduce SANA-Video, a small diffusion model that can efficiently generate videos up to 720x1280 resolution and minute-length duration. SANA-Video synthesizes high-resolution,…

cs.CV2025

Lyra: Generative 3D Scene Reconstruction via Video Diffusion Model Self-Distillation

Sherwin Bahmani, Tianchang Shen, Jiawei Ren +10

The ability to generate virtual environments is crucial for applications ranging from gaming to physical AI domains such as robotics, autonomous driving, and industrial AI. Current…

cs.CV2025

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…

cs.CV2025

Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation Models

Xuanchi Ren, Yifan Lu, Tianshi Cao +13

Collecting and annotating real-world data for safety-critical physical AI systems, such as Autonomous Vehicle (AV), is time-consuming and costly. It is especially challenging to ca…

cs.CV2025★ 2 cited

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…

cs.CV2025

GEN3C: 3D-Informed World-Consistent Video Generation with Precise Camera Control

Xuanchi Ren, Tianchang Shen, Jiahui Huang +7

We present GEN3C, a generative video model with precise Camera Control and temporal 3D Consistency. Prior video models already generate realistic videos, but they tend to leverage…

cs.CV2025

Difix3D+: Improving 3D Reconstructions with Single-Step Diffusion Models

Jay Zhangjie Wu, Yuxuan Zhang, Haithem Turki +6

Neural Radiance Fields and 3D Gaussian Splatting have revolutionized 3D reconstruction and novel-view synthesis task. However, achieving photorealistic rendering from extreme novel…

cs.CV2025★ 1 cited

DiffusionRenderer: Neural Inverse and Forward Rendering with Video Diffusion Models

Ruofan Liang, Zan Gojcic, Huan Ling +8

Understanding and modeling lighting effects are fundamental tasks in computer vision and graphics. Classic physically-based rendering (PBR) accurately simulates the light transport…

cs.CV2025★ 11 cited

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…