
LaneRCNN: Distributed Representations for GraphCentric Motion Forecasting
Forecasting the future behaviors of dynamic actors is an important task ...
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LookOut: Diverse MultiFuture Prediction and Planning for SelfDriving
Selfdriving vehicles need to anticipate a diverse set of future traffic...
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SafetyOriented Pedestrian Motion and Scene Occupancy Forecasting
In this paper, we address the important problem in selfdriving of forec...
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A PACBayesian Approach to Generalization Bounds for Graph Neural Networks
In this paper, we derive generalization bounds for the two primary class...
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GeoNet++: Iterative Geometric Neural Network with EdgeAware Refinement for Joint Depth and Surface Normal Estimation
In this paper, we propose a geometric neural network with edgeaware ref...
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DSDNet: Deep Structured selfDriving Network
In this paper, we propose the Deep Structured selfDriving Network (DSDN...
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Testing the Safety of Selfdriving Vehicles by Simulating Perception and Prediction
We present a novel method for testing the safety of selfdriving vehicle...
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Learning Lane Graph Representations for Motion Forecasting
We propose a motion forecasting model that exploits a novel structured m...
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Implicit Latent Variable Model for SceneConsistent Motion Forecasting
In order to plan a safe maneuver an autonomous vehicle must accurately p...
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Fast and Accurate: Structure Coherence Component for Face Alignment
In this paper, we propose a fast and accurate coordinate regression meth...
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Latent Variable Modelling with Hyperbolic Normalizing Flows
The choice of approximate posterior distributions plays a central role i...
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Nonlinear Equation Solving: A Faster Alternative to Feedforward Computation
Feedforward computations, such as evaluating a neural network or samplin...
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SpatiallyAware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data
In this paper, we tackle the problem of relational behavior forecasting ...
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Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction
Selfdriving vehicles plan around both static and dynamic objects, apply...
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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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DMMNet: Differentiable MaskMatching Network for Video Object Segmentation
In this paper, we propose the differentiable maskmatching network (DMM...
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Deformable Filter Convolution for Point Cloud Reasoning
Point clouds are the native output of many realworld 3D sensors. To bor...
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Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models
We introduce a new molecular dataset, named Alchemy, for developing mach...
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DARNet: Deep Active Ray Network for Building Segmentation
In this paper, we propose a Deep Active Ray Network (DARNet) for automat...
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UPSNet: A Unified Panoptic Segmentation Network
In this paper, we propose a unified panoptic segmentation network (UPSNe...
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LanczosNet: MultiScale Deep Graph Convolutional Networks
We propose the Lanczos network (LanczosNet), which uses the Lanczos algo...
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Incremental FewShot Learning with Attention Attractor Networks
Machine learning classifiers are often trained to recognize a set of pre...
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Neural Guided Constraint Logic Programming for Program Synthesis
Synthesizing programs using example input/outputs is a classic problem i...
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Inference in Probabilistic Graphical Models by Graph Neural Networks
A useful computation when acting in a complex environment is to infer th...
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Reviving and Improving Recurrent BackPropagation
In this paper, we revisit the recurrent backpropagation (RBP) algorithm...
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Learning deep structured active contours endtoend
The world is covered with millions of buildings, and precisely knowing e...
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Graph Partition Neural Networks for SemiSupervised Classification
We present graph partition neural networks (GPNN), an extension of graph...
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Understanding ShortHorizon Bias in Stochastic MetaOptimization
Careful tuning of the learning rate, or even schedules thereof, can be c...
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Situation Recognition with Graph Neural Networks
We address the problem of recognizing situations in images. Given an ima...
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Detailrevealing Deep Video Superresolution
Previous CNNbased video superresolution approaches need to align multi...
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Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes
Normalization techniques have only recently begun to be exploited in sup...
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Renjie Liao
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