Renjie Liao
Renjie Liao
在 cs.toronto.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Detail-revealing deep video super-resolution
X Tao, H Gao, R Liao, J Wang, J Jia
Proceedings of the IEEE International Conference on Computer Vision, 4472-4480, 2017
2512017
3d graph neural networks for rgbd semantic segmentation
X Qi, R Liao, J Jia, S Fidler, R Urtasun
Proceedings of the IEEE International Conference on Computer Vision, 5199-5208, 2017
2432017
Video super-resolution via deep draft-ensemble learning
R Liao, X Tao, R Li, Z Ma, J Jia
Proceedings of the IEEE International Conference on Computer Vision, 531-539, 2015
1782015
Geonet: Geometric neural network for joint depth and surface normal estimation
X Qi, R Liao, Z Liu, R Urtasun, J Jia
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
1662018
Deep edge-aware filters
L Xu, J Ren, Q Yan, R Liao, J Jia
International Conference on Machine Learning, 1669-1678, 2015
1642015
Upsnet: A unified panoptic segmentation network
Y Xiong, R Liao, H Zhao, R Hu, M Bai, E Yumer, R Urtasun
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
1362019
Learning Important Spatial Pooling Regions for Scene Classification
D Lin, C Lu, R Liao, J Jia
IEEE Computer Vision and Pattern Recognition, 2014
1202014
Handling motion blur in multi-frame super-resolution
Z Ma, R Liao, X Tao, L Xu, J Jia, E Wu
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015
1132015
Learning to generate images with perceptual similarity metrics
J Snell, K Ridgeway, R Liao, B Roads, MC Mozer, RS Zemel
IEEE International Conference on Image Processing, 2017
105*2017
Lanczosnet: Multi-scale deep graph convolutional networks
R Liao, Z Zhao, R Urtasun, RS Zemel
International Conference on Learning Representations, 2019
972019
Nervenet: Learning structured policy with graph neural networks
T Wang, R Liao, J Ba, S Fidler
International Conference on Learning Representations, 2018
922018
Situation recognition with graph neural networks
R Li, M Tapaswi, R Liao, J Jia, R Urtasun, S Fidler
Proceedings of the IEEE International Conference on Computer Vision, 4173-4182, 2017
842017
Learning deep structured active contours end-to-end
D Marcos, D Tuia, B Kellenberger, L Zhang, M Bai, R Liao, R Urtasun
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
772018
Learning deep parsimonious representations
R Liao, A Schwing, R Zemel, R Urtasun
Advances in Neural Information Processing Systems, 5076-5084, 2016
712016
Normalizing the normalizers: Comparing and extending network normalization schemes
M Ren, R Liao, R Urtasun, FH Sinz, RS Zemel
International Conference on Learning Representations, 2016
682016
Efficient graph generation with graph recurrent attention networks
R Liao, Y Li, Y Song, S Wang, C Nash, WL Hamilton, D Duvenaud, ...
Advances in Neural Information Processing Systems 32, 4255--4265, 2019
602019
Incremental few-shot learning with attention attractor networks
M Ren, R Liao, E Fetaya, RS Zemel
Advances in Neural Information Processing Systems 32, 5275--5285, 2019
562019
Understanding short-horizon bias in stochastic meta-optimization
Y Wu, M Ren, R Liao, R Grosse
International Conference on Learning Representations, 2018
512018
SpAGNN: Spatially-aware graph neural networks for relational behavior forecasting from sensor data
S Casas, C Gulino, R Liao, R Urtasun
2020 IEEE International Conference on Robotics and Automation (ICRA), 9491-9497, 2020
47*2020
Inference in probabilistic graphical models by graph neural networks
KJ Yoon, R Liao, Y Xiong, L Zhang, E Fetaya, R Urtasun, R Zemel, ...
2019 53rd Asilomar Conference on Signals, Systems, and Computers, 868-875, 2019
422019
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