5 papers
Representation Distribution Matching for One-Step Visual Generation
Lan Feng, Wuyang Li, Eloi Zablocki +2
We elucidate the design space of Representation Distribution Matching (RDM), our name for the paradigm that trains a one-step image generator by matching generated and reference fe…
Position: Mind the Gap-AI Security and the Limits of Current Reporting Standards
Lukas Bieringer, Sean McGregor, Nicole Nichols +5
AI systems face a growing number of AI security threats that are increasingly exploited in the real world. Hence, shared AI incident reporting practices are emerging in industry as…
RAP: 3D Rasterization Augmented End-to-End Planning
Lan Feng, Yang Gao, Eloi Zablocki +5
Imitation learning for end-to-end driving trains policies only on expert demonstrations. Once deployed in a closed loop, such policies lack recovery data: small mistakes cannot be…
MAD: Motion Appearance Decoupling for efficient Driving World Models
Ahmad Rahimi, Valentin Gerard, Eloi Zablocki +2
Recent video diffusion models generate photorealistic, temporally coherent videos, yet they fall short as reliable world models for autonomous driving, where structured motion and…
Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting
Kaouther Messaoud, Matthieu Cord, Alexandre Alahi
Existing vehicle trajectory prediction models struggle with generalizability, prediction uncertainties, and handling complex interactions. It is often due to limitations like compl…