1 citations · 1 across the 4 of their papers we have counts for
5 papers
ScenarioControl: Vision-Language Controllable Vectorized Latent Scenario Generation
Lili Gao, Yanbo Xu, William Koch +8
We introduce ScenarioControl, the first vision-language control mechanism for learned driving scenario generation. Given a text prompt or an input image, Scenario-Control synthesiz…
ChopGrad: Pixel-Wise Losses for Latent Video Diffusion via Truncated Backpropagation
Dmitriy Rivkin, Parker Ewen, Lili Gao +5
Recent video diffusion models achieve high-quality generation through recurrent frame processing where each frame generation depends on previous frames. However, this recurrent mec…
VERDI: VLM-Embedded Reasoning for Autonomous Driving
Bowen Feng, Zhiting Mei, Julian Ost +5
While autonomous driving (AD) stacks struggle with decision making under partial observability and real-world complexity, human drivers are capable of applying commonsense reasonin…
WorldFlow3D: Flowing Through 3D Distributions for Unbounded World Generation
Amogh Joshi, Julian Ost, Felix Heide
Unbounded 3D world generation is emerging as a foundational task for scene modeling in computer vision, graphics, and robotics. In this work, we present WorldFlow3D, a novel method…
LSD-3D: Large-Scale 3D Driving Scene Generation with Geometry Grounding
Julian Ost, Andrea Ramazzina, Amogh Joshi +3
Large-scale scene data is essential for training and testing in robot learning. Neural reconstruction methods have promised the capability of reconstructing large physically-ground…