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NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image Generation



Xiaohui Zeng , Raquel Urtasun , Richard Zemel , Sanja Fidler , Renjie Liao

* UAI2021, code at https://github.com/ZENGXH/NPDRAW 

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NP-DRAW: A Non-Parametric Structured Latent Variable Modelfor Image Generation



Xiaohui Zeng , Raquel Urtasun , Richard Zemel , Sanja Fidler , Renjie Liao

* UAI2021, code at https://github.com/ZENGXH/NPDRAW 

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LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting



Wenyuan Zeng , Ming Liang , Renjie Liao , Raquel Urtasun


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



Alexander Cui , Abbas Sadat , Sergio Casas , Renjie Liao , Raquel Urtasun


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Safety-Oriented Pedestrian Motion and Scene Occupancy Forecasting



Katie Luo , Sergio Casas , Renjie Liao , Xinchen Yan , Yuwen Xiong , Wenyuan Zeng , Raquel Urtasun


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



Renjie Liao , Raquel Urtasun , Richard Zemel


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



Xiaojuan Qi , Zhengzhe Liu , Renjie Liao , Philip H. S. Torr , Raquel Urtasun , Jiaya Jia

* TPAMI 2020. Code available: https://github.com/xjqi/GeoNet 

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DSDNet: Deep Structured self-Driving Network



Wenyuan Zeng , Shenlong Wang , Renjie Liao , Yun Chen , Bin Yang , Raquel Urtasun

* ECCV 2020 

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



Kelvin Wong , Qiang Zhang , Ming Liang , Bin Yang , Renjie Liao , Abbas Sadat , Raquel Urtasun

* ECCV 2020 

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Learning Lane Graph Representations for Motion Forecasting



Ming Liang , Bin Yang , Rui Hu , Yun Chen , Renjie Liao , Song Feng , Raquel Urtasun

* ECCV 2020 Oral 

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