87 citations · 97 across the 9 of their papers we have counts for
4 papers · 1 filter
Generating Useful Accident-Prone Driving Scenarios via a Learned Traffic Prior
Davis Rempe, Jonah Philion, Leonidas J. Guibas +2
Evaluating and improving planning for autonomous vehicles requires scalable generation of long-tail traffic scenarios. To be useful, these scenarios must be realistic and challengi…
Towards Optimal Strategies for Training Self-Driving Perception Models in Simulation
David Acuna, Jonah Philion, Sanja Fidler
Autonomous driving relies on a huge volume of real-world data to be labeled to high precision. Alternative solutions seek to exploit driving simulators that can generate large amou…
Learning Indoor Inverse Rendering with 3D Spatially-Varying Lighting
Zian Wang, Jonah Philion, Sanja Fidler +1
In this work, we address the problem of jointly estimating albedo, normals, depth and 3D spatially-varying lighting from a single image. Most existing methods formulate the task as…
DriveGAN: Towards a Controllable High-Quality Neural Simulation
Seung Wook Kim, Jonah Philion, Antonio Torralba +1
Realistic simulators are critical for training and verifying robotics systems. While most of the contemporary simulators are hand-crafted, a scaleable way to build simulators is to…