World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
6865
World Ranking
8862
National Ranking
352

Overview

Renjie Liao is affiliated with the University of British Columbia in Canada. Their research primarily spans the fields of Computer Science and Engineering, with publications notably focused on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Automotive Engineering, Cardiology and Cardiovascular Medicine, and Computational Mechanics.

Their work broadly covers multiple research topics including Autonomous Vehicle Technology and Safety, Anomaly Detection Techniques and Applications, Domain Adaptation and Few-Shot Learning, Video Surveillance and Tracking Methods, Multimodal Machine Learning Applications, 3D Shape Modeling and Analysis, and Advanced Neural Network Applications.

Some recent papers authored or co-authored by Renjie Liao include:

  • LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • GeoNet++: Iterative Geometric Neural Network with Edge-Aware Refinement for Joint Depth and Surface Normal Estimation, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Structure-Coherent Deep Feature Learning for Robust Face Alignment, 2021, IEEE Transactions on Image Processing
  • Learning Lane Graph Representations for Motion Forecasting, 2020, arXiv (Cornell University)

Renjie Liao frequently collaborates with a group of co-authors, including Raquel Urtasun, Ming Liang, Leonid Sigal, Teresa S.M. Tsang, and Purang Abolmaesumi.

Their publications appear regularly in several venues, with the most frequent being arXiv (Cornell University), where they have contributed 40 papers. Other notable publication venues include the 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), the 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Lecture Notes in Computer Science, and the 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Best Publications

  • Learning Lane Graph Representations for Motion Forecasting

    Ming Liang;Bin Yang;Rui Hu;Yun Chen

  • Detail-Revealing Deep Video Super-Resolution

    Xin Tao;Hongyun Gao;Renjie Liao;Jue Wang

  • 3D Graph Neural Networks for RGBD Semantic Segmentation

    Xiaojuan Qi;Renjie Liao;Jiaya Jia;Sanja Fidler

  • UPSNet: A Unified Panoptic Segmentation Network

    Yuwen Xiong;Renjie Liao;Hengshuang Zhao;Rui Hu

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

    Xiaojuan Qi;Renjie Liao;Zhengzhe Liu;Raquel Urtasun

  • Video Super-Resolution via Deep Draft-Ensemble Learning

    Renjie Liao;Xin Tao;Ruiyu Li;Ziyang Ma

  • Deep Edge-Aware Filters

    Li Xu;Jimmy Ren;Qiong Yan;Renjie Liao

  • Efficient Graph Generation with Graph Recurrent Attention Networks

    Renjie Liao;Renjie Liao;Yujia Li;Yang Song;Shenlong Wang;Shenlong Wang

  • LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting.

    Wenyuan Zeng;Ming Liang;Renjie Liao;Raquel Urtasun

  • LanczosNet: Multi-Scale Deep Graph Convolutional Networks

    Renjie Liao;Renjie Liao;Zhizhen Zhao;Raquel Urtasun;Raquel Urtasun;Richard S. Zemel;Richard S. Zemel

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

    Sergio Casas;Cole Gulino;Renjie Liao;Raquel Urtasun

  • NerveNet: Learning Structured Policy with Graph Neural Networks

    Tingwu Wang;Renjie Liao;Jimmy Ba;Sanja Fidler

  • Learning to generate images with perceptual similarity metrics

    Jake Snell;Karl Ridgeway;Renjie Liao;Brett D. Roads

  • Handling motion blur in multi-frame super-resolution

    Ziyang Ma;Renjie Liao;Xin Tao;Li Xu

  • Learning Deep Structured Active Contours End-to-End

    Lisa Zhang;Min Bai;Renjie Liao;Raquel Urtasun

  • Learning Important Spatial Pooling Regions for Scene Classification

    Di Lin;Cewu Lu;Renjie Liao;Jiaya Jia

  • Situation Recognition with Graph Neural Networks

    Ruiyu Li;Makarand Tapaswi;Renjie Liao;Jiaya Jia

  • DARNet: Deep Active Ray Network for Building Segmentation

    Dominic Cheng;Renjie Liao;Sanja Fidler;Raquel Urtasun

  • Implicit Latent Variable Model for Scene-Consistent Motion Forecasting

    Sergio Casas;Cole Gulino;Simon Suo;Katie Luo

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

    Alexander Cui;Sergio Casas;Abbas Sadat;Renjie Liao

  • Understanding Short-Horizon Bias in Stochastic Meta-Optimization

    Yuhuai Wu;Mengye Ren;Renjie Liao;Roger B. Grosse

  • Efficient Graph Generation with Graph Recurrent Attention Networks

    Renjie Liao;Yujia Li;Yang Song;Shenlong Wang

Frequent Co-Authors

Raquel Urtasun
Raquel Urtasun University of Toronto
Richard S. Zemel
Richard S. Zemel University of Toronto
Jiaya Jia
Jiaya Jia Hong Kong University of Science and Technology
Sanja Fidler
Sanja Fidler University of Toronto
Michael C. Mozer
Michael C. Mozer Google (United States)
Xiaojuan Qi
Xiaojuan Qi University of Hong Kong
Stefano Ermon
Stefano Ermon Stanford University
Jianping Shi
Jianping Shi SenseTime
David Duvenaud
David Duvenaud University of Toronto
Hengshuang Zhao
Hengshuang Zhao University of Hong Kong

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