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Raquel Urtasun

Recent publications

Efficient Graph Generation with Graph Recurrent Attention Networks

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Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehicles

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Exploiting Sparse Semantic HD Maps for Self-Driving Vehicle Localization

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Identifying Unknown Instances for Autonomous Driving

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Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction

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DSIC: Deep Stereo Image Compression

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Learning Joint 2D-3D Representations for Depth Completion

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DAGMapper: Learning to Map by Discovering Lane Topology

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DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation

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DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch

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End-to-End Interpretable Neural Motion Planner

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UPSNet: A Unified Panoptic Segmentation Network

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Convolutional Recurrent Network for Road Boundary Extraction

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Learning to Localize Through Compressed Binary Maps

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Multi-Task Multi-Sensor Fusion for 3D Object Detection

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DARNet: Deep Active Ray Network for Building Segmentation

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Deep Rigid Instance Scene Flow

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DeepSignals: Predicting Intent of Drivers Through Visual Signals

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LanczosNet: Multi-Scale Deep Graph Convolutional Networks

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Graph HyperNetworks for Neural Architecture Search

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Dimensionality Reduction for Representing the Knowledge of Probabilistic Models

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Neural Guided Constraint Logic Programming for Program Synthesis

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Deep Multi-Sensor Lane Detection

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IntentNet: Learning to Predict Intention from Raw Sensor Data

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HDNET: Exploiting HD Maps for 3D Object Detection

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Learning to Localize Using a LiDAR Intensity Map

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Efficient Convolutions for Real-Time Semantic Segmentation of 3D Point Clouds

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Single Image Intrinsic Decomposition Without a Single Intrinsic Image

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Deep Continuous Fusion for Multi-Sensor 3D Object Detection

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End-to-End Deep Structured Models for Drawing Crosswalks

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PIXOR: Real-Time 3D Object Detection from Point Clouds

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Learning Deep Structured Active Contours End-to-End

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Matching Adversarial Networks

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SurfConv: Bridging 3D and 2D Convolution for RGBD Images

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SBNet: Sparse Blocks Network for Fast Inference

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Hierarchical Recurrent Attention Networks for Structured Online Maps

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Deep Parametric Continuous Convolutional Neural Networks

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

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GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation

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MultiNet: Real-Time Joint Semantic Reasoning for Autonomous Driving

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End-to-End Learning of Multi-Sensor 3D Tracking by Detection

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Learning to Reweight Examples for Robust Deep Learning

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Reviving and Improving Recurrent Back-Propagation

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Inference in Probabilistic Graphical Models by Graph Neural Networks

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Leveraging Constraint Logic Programming for Neural Guided Program Synthesis

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Graph Partition Neural Networks for Semi-Supervised Classification

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The Reversible Residual Network: Backpropagation Without Storing Activations

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Few-Shot Learning Through an Information Retrieval Lens

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Situation Recognition with Graph Neural Networks

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TorontoCity: Seeing the World with a Million Eyes

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Be Your Own Prada: Fashion Synthesis with Structural Coherence

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SGN: Sequential Grouping Networks for Instance Segmentation

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3D Graph Neural Networks for RGBD Semantic Segmentation

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Towards Diverse and Natural Image Descriptions via a Conditional GAN

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DeepRoadMapper: Extracting Road Topology from Aerial Images

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Efficient Multiple Instance Metric Learning Using Weakly Supervised Data

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Annotating Object Instances with a Polygon-RNN

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Deep Watershed Transform for Instance Segmentation

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Sports Field Localization via Deep Structured Models

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Deep Spectral Clustering Learning

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Find Your Way by Observing the Sun and Other Semantic Cues

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Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes

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