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Deep Feedback Inverse Problem Solver
We present an efficient, effective, and generic approach towards solving...
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Non-parametric Memory for Spatio-Temporal Segmentation of Construction Zones for Self-Driving
In this paper, we introduce a non-parametric memory representation for s...
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Secrets of 3D Implicit Object Shape Reconstruction in the Wild
Reconstructing high-fidelity 3D objects from sparse, partial observation...
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Deep Parametric Continuous Convolutional Neural Networks
Standard convolutional neural networks assume a grid structured input is...
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S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modeling
Constructing and animating humans is an important component for building...
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Asynchronous Multi-View SLAM
Existing multi-camera SLAM systems assume synchronized shutters for all ...
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GeoSim: Photorealistic Image Simulation with Geometry-Aware Composition
Scalable sensor simulation is an important yet challenging open problem ...
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SceneGen: Learning to Generate Realistic Traffic Scenes
We consider the problem of generating realistic traffic scenes automatic...
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Pit30M: A Benchmark for Global Localization in the Age of Self-Driving Cars
We are interested in understanding whether retrieval-based localization ...
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Convolutional Recurrent Network for Road Boundary Extraction
Creating high definition maps that contain precise information of static...
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Deep Continuous Fusion for Multi-Sensor 3D Object Detection
In this paper, we propose a novel 3D object detector that can exploit bo...
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Learning to Localize Through Compressed Binary Maps
One of the main difficulties of scaling current localization systems to ...
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Learning to Localize Using a LiDAR Intensity Map
In this paper we propose a real-time, calibration-agnostic and effective...
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MuSCLE: Multi Sweep Compression of LiDAR using Deep Entropy Models
We present a novel compression algorithm for reducing the storage of LiD...
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Conditional Entropy Coding for Efficient Video Compression
We propose a very simple and efficient video compression framework that ...
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DSDNet: Deep Structured self-Driving Network
In this paper, we propose the Deep Structured self-Driving Network (DSDN...
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LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World
We tackle the problem of producing realistic simulations of LiDAR point ...
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OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression
We present a novel deep compression algorithm to reduce the memory footp...
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Identifying Unknown Instances for Autonomous Driving
In the past few years, we have seen great progress in perception algorit...
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Efficient Graph Generation with Graph Recurrent Attention Networks
We propose a new family of efficient and expressive deep generative mode...
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DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch
Our goal is to significantly speed up the runtime of current state-of-th...
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DSIC: Deep Stereo Image Compression
In this paper we tackle the problem of stereo image compression, and lev...
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Exploiting Sparse Semantic HD Maps for Self-Driving Vehicle Localization
In this paper we propose a novel semantic localization algorithm that ex...
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Deep Multi-Sensor Lane Detection
Reliable and accurate lane detection has been a long-standing problem in...
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Deep Rigid Instance Scene Flow
In this paper we tackle the problem of scene flow estimation in the cont...
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TorontoCity: Seeing the World with a Million Eyes
In this paper we introduce the TorontoCity benchmark, which covers the f...
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AutoScaler: Scale-Attention Networks for Visual Correspondence
Finding visual correspondence between local features is key to many comp...
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Find your Way by Observing the Sun and Other Semantic Cues
In this paper we present a robust, efficient and affordable approach to ...
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