activity
20122021
most citedDomain Adaptations for Computer Vision Applications

28 citations · 44 across the 3 of their papers we have counts for

collaborators

7 papers

cs.LG2021

The Reasonable Crowd: Towards evidence-based and interpretable models of driving behavior

Bassam Helou, Aditya Dusi, Anne Collin +7

Autonomous vehicles must balance a complex set of objectives. There is no consensus on how they should do so, nor on a model for specifying a desired driving behavior. We created a…

cs.CV202116 cited

Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversals

Nachiket Deo, Eric M. Wolff, Oscar Beijbom

Accurately predicting the future motion of surrounding vehicles requires reasoning about the inherent uncertainty in driving behavior. This uncertainty can be loosely decoupled int…

cs.LG2019

CoverNet: Multimodal Behavior Prediction using Trajectory Sets

Tung Phan-Minh, Elena Corina Grigore, Freddy A. Boulton +2

We present CoverNet, a new method for multimodal, probabilistic trajectory prediction for urban driving. Previous work has employed a variety of methods, including multimodal regre…

cs.CV2019

PointPainting: Sequential Fusion for 3D Object Detection

Sourabh Vora, Alex H. Lang, Bassam Helou +1

Camera and lidar are important sensor modalities for robotics in general and self-driving cars in particular. The sensors provide complementary information offering an opportunity…

cs.LG2019

nuScenes: A multimodal dataset for autonomous driving

Holger Caesar, Varun Bankiti, Alex H. Lang +7

Robust detection and tracking of objects is crucial for the deployment of autonomous vehicle technology. Image based benchmark datasets have driven development in computer vision t…

cs.LG2018

PointPillars: Fast Encoders for Object Detection from Point Clouds

Alex H. Lang, Sourabh Vora, Holger Caesar +3

Object detection in point clouds is an important aspect of many robotics applications such as autonomous driving. In this paper we consider the problem of encoding a point cloud in…