Skip to main content
All
Clear valueopen
Most relevant
Clear valueopen

1762 results for "airport" across all locations

Uber AI, Engineering 1May,2019 / Global

UPSNet: A Unified Panoptic Segmentation Network

Y. Xiong, R. Liao, H. Zhao, R. Hu, M. Bai, E. Yumer, R. Urtasun
In this paper we tackle the problem of scene flow estimation in the context of self-driving. We leverage deep learning techniques as well as strong priors as in our application domain the motion of the scene can be composed by the motion of the robot and the 3D motion of the actors in the scene. […] [PDF]
Conference on Computer Vision and Pattern Recognition (CVPR), 2019

Uber AI, Engineering 1June,2018 / Global

Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net

W. Luo, B. Yang, R. Urtasun
In this paper we propose a novel deep neural network that is able to jointly reason about 3D detection, tracking and motion forecasting given data captured by a 3D sensor. By jointly reasoning about these tasks, our holistic approach is more robust to occlusion as well as sparse data at range. […] [PDF]
Conference on Computer Vision and Pattern Recognition (CVPR), 2018

Uber AI, Engineering 1October,2018 / Global

HDNET: Exploiting HD Maps for 3D Object Detection

B. Yang, M. Liang, R. Urtasun
In this paper we show that High-Definition (HD) maps provide strong priors that can boost the performance and robustness of modern 3D object detectors. Towards this goal, we design a single stage detector that extracts geometric and semantic features from the HD maps. […] [PDF]
Conference on Robot Learning (CORL), 2018

Uber AI, Engineering 1December,2018 / Global

Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets

F. Chou, T.-H. Lin, H. Cui, V. Radosavljevic, T. Nguyen, T. Huang, M. Niedoba, J. Schneider, N. Djuric
Following detection and tracking of traffic actors, prediction of their future motion is the next critical component of a self-driving vehicle (SDV), allowing the SDV to move safely and efficiently in its environment. This is particularly important when it comes to vulnerable road users (VRUs), such as pedestrians and bicyclists. We present a deep learning method for predicting VRU movement where we rasterize high-definition maps and actor’s surroundings into bird’s-eye view image used as input to convolutional networks. […] [PDF]
MLITS workshop @ Neural Information Processing Systems (NeurIPS), 2018

Post thumbnail
Promotions 17June,2016 / Cincinnati

Supporting Cincinnati’s LGBT Community

Products 27February,2017 / Georgia

Tell the Georgia Legislature: Don’t Tax My Ride

Post thumbnail
Promotions 4October,2016 / Saudi Arabia

Free Rides to Drive Away Breast Cancer

Post thumbnail
Promotions 26February,2016 / Kenya

#ProTips for Uber Trips: Personalize your Referral Code & Earn FREE Rides!

Post thumbnail
Promotions 17June,2016 / California

Supporting Orange County’s LGBT Community

Post thumbnail
Drive 15October,2018 / France

La première impression, là où tout se joue !

Créer une ambiance agréable dans son véhicule en quelques secondes ? Pour fournir un service de qualité, retrouvez les meilleurs conseils à appliquer

110
open