4 citations · 4 across the 1 of their papers we have counts for
3 papers
Linear Memory SE(2) Invariant Attention
Ethan Pronovost, Neha Boloor, Peter Schleede +3
Processing spatial data is a key component in many learning tasks for autonomous driving such as motion forecasting, multi-agent simulation, and planning. Prior works have demonstr…
Scenario Diffusion: Controllable Driving Scenario Generation With Diffusion
Ethan Pronovost, Meghana Reddy Ganesina, Noureldin Hendy +4
Automated creation of synthetic traffic scenarios is a key part of validating the safety of autonomous vehicles (AVs). In this paper, we propose Scenario Diffusion, a novel diffusi…
Generating Driving Scenes with Diffusion
Ethan Pronovost, Kai Wang, Nick Roy
In this paper we describe a learned method of traffic scene generation designed to simulate the output of the perception system of a self-driving car. In our "Scene Diffusion" syst…