Autonomous Vehicles

IDA-3D: Instance-Depth-Aware 3D Object Detection From Stereo Vision for Autonomous Driving CVPR 2020 Integrating Egocentric Localization for More Realistic Point-Goal Navigation Agents CoRL 2020 Iterative Semi-parametric Dynamics Model Learning For Autonomous Racing CoRL 2020 Just Go With the Flow: Self-Supervised Scene Flow Estimation CVPR 2020 KFNet: Learning Temporal Camera Relocalization Using Kalman Filtering CVPR 2020 Lane detection using lane boundary marker network with road geometry constraints WACV 2020 Learning a Decision Module by Imitating Driver’s Control Behaviors CoRL 2020 Learning Situational Driving CVPR 2020 Learning To Explore Using Active Neural SLAM ICLR 2020 Learning to Follow Directions in Street View AAAI 2020 LiDAR-Based Online 3D Video Object Detection With Graph-Based Message Passing and Spatiotemporal Transformer Attention CVPR 2020 LiRaNet: End-to-End Trajectory Prediction using Spatio-Temporal Radar Fusion CoRL 2020 Looking Ahead: Anticipating Pedestrians Crossing with Future Frames Prediction WACV 2020 "Looking at the Right Stuff" - Guided Semantic-Gaze for Autonomous Driving CVPR 2020 MANTRA: Memory Augmented Networks for Multiple Trajectory Prediction CVPR 2020 Mixed Strategies for Robust Optimization of Unknown Objectives AISTATS 2020 Modeling Perception Errors towards Robust Decision Making in Autonomous Vehicles IJCAI 2020 MonoLayout: Amodal scene layout from a single image WACV 2020 MRFMap: Online Probabilistic 3D Mapping using Forward Ray Sensor Models RSS 2020 Multi-Agent Routing Value Iteration Network ICML 2020 Multi-Fidelity Black-Box Optimization for Time-Optimal Quadrotor Maneuvers RSS 2020 Multimodal Future Localization and Emergence Prediction for Objects in Egocentric View With a Reachability Prior CVPR 2020 Multimodal Interaction-Aware Trajectory Prediction in Crowded Space AAAI 2020 Multi-Robot Collision Avoidance under Uncertainty with Probabilistic Safety Barrier Certificates NeurIPS 2020 NeoNav: Improving the Generalization of Visual Navigation via Generating Next Expected Observations AAAI 2020