Renjie Liao
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
62
Venues
19
Active years
2010–2025
Best venue rank
A*
Where they publish
Papers
62 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | CVPR | MoFlow: One-Step Flow Matching for Human Trajectory Forecasting via Implicit Maximum Likelihood Estimation based Distillation. | Yuxiang Fu, Qi Yan, Lele Wang, Ke Li, Renjie Liao |
| 2025 | CVPR | LatentHOI: On the Generalizable Hand Object Motion Generation with Latent Hand Diffusion. | Muchen Li, Sammy Christen, Chengde Wan, Yujun Cai, Renjie Liao, Leonid Sigal, Shugao Ma |
| 2025 | EMNLP | Test-Time Steering for Lossless Text Compression via Weighted Product of Experts. | Qihang Zhang, Muchen Li, Ziao Wang, Renjie Liao, Lele Wang |
| 2025 | ICLR | SymmetricDiffusers: Learning Discrete Diffusion on Finite Symmetric Groups. | Yongxing Zhang, Donglin Yang, Renjie Liao |
| 2025 | ICML | Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant Evaluation. | Sadegh Mahdavi, Muchen Li, Kaiwen Liu, Christos Thrampoulidis, Leonid Sigal, Renjie Liao |
| 2025 | IROS | TrajFlow: Multi-modal Motion Prediction via Flow Matching. | Qi Yan, Brian Zhang, Yutong Zhang, Daniel Yang, Joshua White, Di Chen, Jiachao Liu, Langechuan Liu, Binnan Zhuang, Shaoshuai Shi, Renjie Liao |
| 2024 | CVPR | Generative 3D Part Assembly via Part-Whole-Hierarchy Message Passing. | Bi'an Du, Xiang Gao, Wei Hu, Renjie Liao |
| 2024 | CVPR | NTIRE 2024 Quality Assessment of AI-Generated Content Challenge. | Xiaohong Liu, Xiongkuo Min, Guangtao Zhai, Chunyi Li, Tengchuan Kou, Wei Sun, Haoning Wu, Yixuan Gao, Yuqin Cao, Zicheng Zhang, Xiele Wu, Radu Timofte, Fei Peng, Huiyuan Fu, Anlong Ming, Chuanming Wang, Huadong Ma, Shuai He, Zifei Dou, Shu Chen, Huacong Zhang, Haiyi Xie, Chengwei Wang, Baoying Chen, Jishen Zeng, Jianquan Yang, Weigang Wang, Xi Fang, Xiaoxin Lv, Jun Yan, Tianwu Zhi, Yabin Zhang, Yaohui Li, Yang Li, Jingwen Xu, Jianzhao Liu, Yiting Liao, Junlin Li, Zihao Yu, Fengbin Guan, Yiting Lu, Xin Li, Hossein Motamednia, S. Farhad Hosseini-Benvidi, Ahmad Mahmoudi-Aznaveh, Azadeh Mansouri, Ganzorig Gankhuyag, Kihwan Yoon, Yifang Xu, Haotian Fan, Fangyuan Kong, Shiling Zhao, Weifeng Dong, Haibing Yin, Li Zhu, Zhiling Wang, Bingchen Huang, Avinab Saha, Sandeep Mishra, Shashank Gupta, Rajesh Sureddi, Oindrila Saha, Luigi Celona, Simone Bianco, Paolo Napoletano, Raimondo Schettini, Junfeng Yang, Jing Fu, Wei Zhang, Wenzhi Cao, Limei Liu, Han Peng, Weijun Yuan, Zhan Li, Yihang Cheng, Yifan Deng, Haohui Li, Bowen Qu, Yao Li, Shuqing Luo, Shunzhou Wang, Wei Gao, Zihao Lu, Marcos V. Conde, Xinrui Wang, Zhibo Chen, Ruling Liao, Yan Ye, Qiulin Wang, Bing Li, Zhaokun Zhou, Miao Geng, Rui Chen, Xin Tao, Xiaoyu Liang, Shangkun Sun, Xingyuan Ma, Jiaze Li, Mengduo Yang, Haoran Xu, Jie Zhou, Shiding Zhu, Bohan Yu, Pengfei Chen, Xinrui Xu, Jiabin Shen, Zhichao Duan, Erfan Asadi, Jiahe Liu, Qi Yan, Youran Qu, Xiaohui Zeng, Lele Wang, Renjie Liao |
| 2024 | ICASSP | Revisiting the Equivalence of In-Context Learning and Gradient Descent: The Impact of Data Distribution. | Sadegh Mahdavi, Renjie Liao, Christos Thrampoulidis |
| 2024 | ICLR | Memorization Capacity of Multi-Head Attention in Transformers. | Sadegh Mahdavi, Renjie Liao, Christos Thrampoulidis |
| 2024 | ICML | Learning Latent Structures in Network Games via Data-Dependent Gated-Prior Graph Variational Autoencoders. | Xue Yu, Muchen Li, Yan Leng, Renjie Liao |
| 2024 | ISIT | An Information-Theoretic Framework for Out-of-Distribution Generalization. | Wenliang Liu, Guanding Yu, Lele Wang, Renjie Liao |
| 2024 | WACV | Self-Supervised Relation Alignment for Scene Graph Generation. | Bicheng Xu, Renjie Liao, Leonid Sigal |
| 2023 | ICLR | Specformer: Spectral Graph Neural Networks Meet Transformers. | Deyu Bo, Chuan Shi, Lele Wang, Renjie Liao |
| 2023 | ICLR | Scaling Forward Gradient With Local Losses. | Mengye Ren, Simon Kornblith, Renjie Liao, Geoffrey E. Hinton |
| 2023 | MICCAI | EchoGLAD: Hierarchical Graph Neural Networks for Left Ventricle Landmark Detection on Echocardiograms. | Masoud Mokhtari, Mobina Mahdavi, Hooman Vaseli, Christina Luong, Purang Abolmaesumi, Teresa S. M. Tsang, Renjie Liao |
| 2023 | WACV | VLC-BERT: Visual Question Answering with Contextualized Commonsense Knowledge. | Sahithya Ravi, Aditya Chinchure, Leonid Sigal, Renjie Liao, Vered Shwartz |
| 2023 | WACV | NeuralBF: Neural Bilateral Filtering for Top-down Instance Segmentation on Point Clouds. | Weiwei Sun, Daniel Rebain, Renjie Liao, Vladimir Tankovich, Soroosh Yazdani, Kwang Moo Yi, Andrea Tagliasacchi |
| 2022 | MICCAI | EchoGNN: Explainable Ejection Fraction Estimation with Graph Neural Networks. | Masoud Mokhtari, Teresa Tsang, Purang Abolmaesumi, Renjie Liao |
| 2021 | ICCV | LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving. | Alexander Cui, Sergio Casas, Abbas Sadat, Renjie Liao, Raquel Urtasun |
| 2021 | ICLR | A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks. | Renjie Liao, Raquel Urtasun, Richard S. Zemel |
| 2021 | ICML | Accelerating Feedforward Computation via Parallel Nonlinear Equation Solving. | Yang Song, Chenlin Meng, Renjie Liao, Stefano Ermon |
| 2021 | IROS | Safety-Oriented Pedestrian Occupancy Forecasting. | Katie Luo, Sergio Casas, Renjie Liao, Xinchen Yan, Yuwen Xiong, Wenyuan Zeng, Raquel Urtasun |
| 2021 | IROS | LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting. | Wenyuan Zeng, Ming Liang, Renjie Liao, Raquel Urtasun |
| 2021 | UAI | NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image Generation. | Xiaohui Zeng, Raquel Urtasun, Richard S. Zemel, Sanja Fidler, Renjie Liao |
| 2020 | ECCV | Implicit Latent Variable Model for Scene-Consistent Motion Forecasting. | Sergio Casas, Cole Gulino, Simon Suo, Katie Luo, Renjie Liao, Raquel Urtasun |
| 2020 | ECCV | Learning Lane Graph Representations for Motion Forecasting. | Ming Liang, Bin Yang, Rui Hu, Yun Chen, Renjie Liao, Song Feng, Raquel Urtasun |
| 2020 | ECCV | 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 |
| 2020 | ECCV | DSDNet: Deep Structured Self-driving Network. | Wenyuan Zeng, Shenlong Wang, Renjie Liao, Yun Chen, Bin Yang, Raquel Urtasun |
| 2020 | ICML | Latent Variable Modelling with Hyperbolic Normalizing Flows. | Avishek Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, William L. Hamilton |
| 2020 | ICRA | SpAGNN: Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data. | Sergio Casas, Cole Gulino, Renjie Liao, Raquel Urtasun |
| 2019 | ACSSC | Inference in Probabilistic Graphical Models by Graph Neural Networks. | KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow |
| 2019 | CoRL | Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction. | Ajay Jain, Sergio Casas, Renjie Liao, Yuwen Xiong, Song Feng, Sean Segal, Raquel Urtasun |
| 2019 | CVPR | DARNet: Deep Active Ray Network for Building Segmentation. | Dominic Cheng, Renjie Liao, Sanja Fidler, Raquel Urtasun |
| 2019 | CVPR | UPSNet: A Unified Panoptic Segmentation Network. | Yuwen Xiong, Renjie Liao, Hengshuang Zhao, Rui Hu, Min Bai, Ersin Yumer, Raquel Urtasun |
| 2019 | ICCV | DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation. | Xiaohui Zeng, Renjie Liao, Li Gu, Yuwen Xiong, Sanja Fidler, Raquel Urtasun |
| 2019 | ICLR | LanczosNet: Multi-Scale Deep Graph Convolutional Networks. | Renjie Liao, Zhizhen Zhao, Raquel Urtasun, Richard S. Zemel |
| 2019 | ICML | Lorentzian Distance Learning for Hyperbolic Representations. | Marc Teva Law, Renjie Liao, Jake Snell, Richard S. Zemel |
| 2018 | CVPR | Learning Deep Structured Active Contours End-to-End. | Diego Marcos, Devis Tuia, Benjamin Kellenberger, Lisa Zhang, Min Bai, Renjie Liao, Raquel Urtasun |
| 2018 | CVPR | GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation. | Xiaojuan Qi, Renjie Liao, Zhengzhe Liu, Raquel Urtasun, Jiaya Jia |
| 2018 | ICLR | Graph Partition Neural Networks for Semi-Supervised Classification. | Renjie Liao, Marc Brockschmidt, Daniel Tarlow, Alexander L. Gaunt, Raquel Urtasun, Richard S. Zemel |
| 2018 | ICLR | NerveNet: Learning Structured Policy with Graph Neural Networks. | Tingwu Wang, Renjie Liao, Jimmy Ba, Sanja Fidler |
| 2018 | ICLR | Understanding Short-Horizon Bias in Stochastic Meta-Optimization. | Yuhuai Wu, Mengye Ren, Renjie Liao, Roger B. Grosse |
| 2018 | ICLR | Inference in probabilistic graphical models by Graph Neural Networks. | KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard S. Zemel, Xaq Pitkow |
| 2018 | ICLR | Leveraging Constraint Logic Programming for Neural Guided Program Synthesis. | Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Raquel Urtasun, Richard S. Zemel |
| 2018 | ICML | Reviving and Improving Recurrent Back-Propagation. | Renjie Liao, Yuwen Xiong, Ethan Fetaya, Lisa Zhang, KiJung Yoon, Xaq Pitkow, Raquel Urtasun, Richard S. Zemel |
| 2017 | ICCV | Situation Recognition with Graph Neural Networks. | Ruiyu Li, Makarand Tapaswi, Renjie Liao, Jiaya Jia, Raquel Urtasun, Sanja Fidler |
| 2017 | ICCV | 3D Graph Neural Networks for RGBD Semantic Segmentation. | Xiaojuan Qi, Renjie Liao, Jiaya Jia, Sanja Fidler, Raquel Urtasun |
| 2017 | ICCV | Detail-Revealing Deep Video Super-Resolution. | Xin Tao, Hongyun Gao, Renjie Liao, Jue Wang, Jiaya Jia |
| 2017 | ICIP | Learning to generate images with perceptual similarity metrics. | Jake Snell, Karl Ridgeway, Renjie Liao, Brett D. Roads, Michael C. Mozer, Richard S. Zemel |
| 2017 | ICLR | Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes. | Mengye Ren, Renjie Liao, Raquel Urtasun, Fabian H. Sinz, Richard S. Zemel |
| 2015 | CVPR | Handling motion blur in multi-frame super-resolution. | Ziyang Ma, Renjie Liao, Xin Tao, Li Xu, Jiaya Jia, Enhua Wu |
| 2015 | ICCV | Video Super-Resolution via Deep Draft-Ensemble Learning. | Renjie Liao, Xin Tao, Ruiyu Li, Ziyang Ma, Jiaya Jia |
| 2015 | ICCV | Semantic Segmentation with Object Clique Potential. | Xiaojuan Qi, Jianping Shi, Shu Liu, Renjie Liao, Jiaya Jia |
| 2015 | ICML | Deep Edge-Aware Filters. | Li Xu, Jimmy S. J. Ren, Qiong Yan, Renjie Liao, Jiaya Jia |
| 2014 | CVPR | Learning Important Spatial Pooling Regions for Scene Classification. | Di Lin, Cewu Lu, Renjie Liao, Jiaya Jia |
| 2014 | ICIP | A confidence growing model for super-resolution. | Sina Lin, Zengchang Qin, Renjie Liao, Tao Wan |
| 2014 | WSDM | Nonparametric bayesian upstream supervised multi-modal topic models. | Renjie Liao, Jun Zhu, Zengchang Qin |
| 2013 | ICASSP | A robust fusion scheme for multifocus images using sparse features. | Tao Wan, Zengchang Qin, Chenchen Zhu, Renjie Liao |
| 2013 | ICCV | CoDeL: A Human Co-detection and Labeling Framework. | Jianping Shi, Renjie Liao, Jiaya Jia |
| 2012 | ACCV | Image Super-Resolution Using Local Learnable Kernel Regression. | Renjie Liao, Zengchang Qin |
| 2010 | ICMLC | A novel serial crime prediction model based on Bayesian learning theory. | Renjie Liao, Xueyao Wang, Lun Li, Zengchang Qin |