2 citations · 2 across the 5 of their papers we have counts for
7 papers
Asset Harvester: Extracting 3D Assets from Autonomous Driving Logs for Simulation
Tianshi Cao, Jiawei Ren, Yuxuan Zhang +12
Closed-loop simulation is a core component of autonomous vehicle (AV) development, enabling scalable testing, training, and safety validation before real-world deployment. Neural s…
Lyra 2.0: Explorable Generative 3D Worlds
Tianchang Shen, Sherwin Bahmani, Kai He +12
Recent advances in video generation enable a new paradigm for 3D scene creation: generating camera-controlled videos that simulate scene walkthroughs, then lifting them to 3D via f…
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…
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…
Masks make discriminative models great again!
Tianshi Cao, Marie-Julie Rakotosaona, Ben Poole +2
We present Image2GS, a novel approach that addresses the challenging problem of reconstructing photorealistic 3D scenes from a single image by focusing specifically on the image-to…
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…