Publications (16)
FastDraw: Addressing the Long Tail of Lane Detection by Adapting a Sequential Prediction Network
Jonah Philion
The search for predictive models that generalize to the long tail of sensor inputs is the central difficulty when developing data-driven models for autonomous vehicles. In this pap…
Learning to Evaluate Perception Models Using Planner-Centric Metrics
Jonah Philion, Amlan Kar, Sanja Fidler
Variants of accuracy and precision are the gold-standard by which the computer vision community measures progress of perception algorithms. One reason for the ubiquity of these met…
Trajeglish: Traffic Modeling as Next-Token Prediction
Jonah Philion, Xue Bin Peng, Sanja Fidler
A longstanding challenge for self-driving development is simulating dynamic driving scenarios seeded from recorded driving logs. In pursuit of this functionality, we apply tools fr…
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…
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…
Wolf: Dense Video Captioning with a World Summarization Framework
Boyi Li, Ligeng Zhu, Ran Tian +20
We propose Wolf, a WOrLd summarization Framework for accurate video captioning. Wolf is an automated captioning framework that adopts a mixture-of-experts approach, leveraging comp…