b'Renjie Liao'

LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting

Forecasting the future behaviors of dynamic actors is an important task ...
01/17/2021 ∙ by Wenyuan Zeng, et al. ∙ 42 ∙ share

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LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving

Self-driving vehicles need to anticipate a diverse set of future traffic...
01/16/2021 ∙ by Alexander Cui, et al. ∙ 8 ∙ share

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Safety-Oriented Pedestrian Motion and Scene Occupancy Forecasting

In this paper, we address the important problem in self-driving of forec...
01/07/2021 ∙ by Katie Luo, et al. ∙ 19 ∙ share

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A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks

In this paper, we derive generalization bounds for the two primary class...
12/14/2020 ∙ by Renjie Liao, et al. ∙ 10 ∙ share

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GeoNet++: Iterative Geometric Neural Network with Edge-Aware Refinement for Joint Depth and Surface Normal Estimation

In this paper, we propose a geometric neural network with edge-aware ref...
12/13/2020 ∙ by Xiaojuan Qi, et al. ∙ 10 ∙ share

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DSDNet: Deep Structured self-Driving Network

In this paper, we propose the Deep Structured self-Driving Network (DSDN...
08/13/2020 ∙ by Wenyuan Zeng, et al. ∙ 5 ∙ share

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Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction

We present a novel method for testing the safety of self-driving vehicle...
08/13/2020 ∙ by Kelvin Wong, et al. ∙ 9 ∙ share

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Learning Lane Graph Representations for Motion Forecasting

We propose a motion forecasting model that exploits a novel structured m...
07/27/2020 ∙ by Ming Liang, et al. ∙ 2 ∙ share

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Implicit Latent Variable Model for Scene-Consistent Motion Forecasting

In order to plan a safe maneuver an autonomous vehicle must accurately p...
07/23/2020 ∙ by Sergio Casas, et al. ∙ 5 ∙ share

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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...
06/21/2020 ∙ by Beier Zhu, et al. ∙ 0 ∙ share

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Latent Variable Modelling with Hyperbolic Normalizing Flows

The choice of approximate posterior distributions plays a central role i...
02/15/2020 ∙ by Avishek Joey Bose, et al. ∙ 10 ∙ share

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Nonlinear Equation Solving: A Faster Alternative to Feedforward Computation

Feedforward computations, such as evaluating a neural network or samplin...
02/10/2020 ∙ by Yang Song, et al. ∙ 40 ∙ share

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Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data

In this paper, we tackle the problem of relational behavior forecasting ...
10/18/2019 ∙ by Sergio Casas, et al. ∙ 31 ∙ share

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Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction

Self-driving vehicles plan around both static and dynamic objects, apply...
10/17/2019 ∙ by Ajay Jain, et al. ∙ 21 ∙ share

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Efficient Graph Generation with Graph Recurrent Attention Networks

We propose a new family of efficient and expressive deep generative mode...
10/02/2019 ∙ by Renjie Liao, et al. ∙ 16 ∙ share

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

In this paper, we propose the differentiable mask-matching network (DMM-...
09/27/2019 ∙ by Xiaohui Zeng, et al. ∙ 8 ∙ share

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Deformable Filter Convolution for Point Cloud Reasoning

Point clouds are the native output of many real-world 3D sensors. To bor...
07/30/2019 ∙ by Yuwen Xiong, et al. ∙ 0 ∙ share

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Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models

We introduce a new molecular dataset, named Alchemy, for developing mach...
06/22/2019 ∙ by Guangyong Chen, et al. ∙ 15 ∙ share

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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...
05/15/2019 ∙ by Dominic Cheng, et al. ∙ 0 ∙ share

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UPSNet: A Unified Panoptic Segmentation Network

In this paper, we propose a unified panoptic segmentation network (UPSNe...
01/12/2019 ∙ by Yuwen Xiong, et al. ∙ 22 ∙ share

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LanczosNet: Multi-Scale Deep Graph Convolutional Networks

We propose the Lanczos network (LanczosNet), which uses the Lanczos algo...
01/06/2019 ∙ by Renjie Liao, et al. ∙ 0 ∙ share

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Incremental Few-Shot Learning with Attention Attractor Networks

Machine learning classifiers are often trained to recognize a set of pre...
10/16/2018 ∙ by Mengye Ren, et al. ∙ 0 ∙ share

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Neural Guided Constraint Logic Programming for Program Synthesis

Synthesizing programs using example input/outputs is a classic problem i...
09/08/2018 ∙ by Lisa Zhang, et al. ∙ 0 ∙ share

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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...
03/21/2018 ∙ by KiJung Yoon, et al. ∙ 0 ∙ share

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Reviving and Improving Recurrent Back-Propagation

In this paper, we revisit the recurrent back-propagation (RBP) algorithm...
03/16/2018 ∙ by Renjie Liao, et al. ∙ 0 ∙ share

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Learning deep structured active contours end-to-end

The world is covered with millions of buildings, and precisely knowing e...
03/16/2018 ∙ by Diego Marcos, et al. ∙ 0 ∙ share

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Graph Partition Neural Networks for Semi-Supervised Classification

We present graph partition neural networks (GPNN), an extension of graph...
03/16/2018 ∙ by Renjie Liao, et al. ∙ 0 ∙ share

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Understanding Short-Horizon Bias in Stochastic Meta-Optimization

Careful tuning of the learning rate, or even schedules thereof, can be c...
03/06/2018 ∙ by Yuhuai Wu, et al. ∙ 0 ∙ share

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Situation Recognition with Graph Neural Networks

We address the problem of recognizing situations in images. Given an ima...
08/14/2017 ∙ by Ruiyu Li, et al. ∙ 0 ∙ share

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Detail-revealing Deep Video Super-resolution

Previous CNN-based video super-resolution approaches need to align multi...
04/10/2017 ∙ by Xin Tao, et al. ∙ 0 ∙ share

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Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes

Normalization techniques have only recently begun to be exploited in sup...
11/14/2016 ∙ by Mengye Ren, et al. ∙ 0 ∙ share

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Renjie Liao

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