Renjie Liao
Renjie Liao
Verified email at cs.toronto.edu - Homepage
Title
Cited by
Cited by
Year
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
2192017
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
1922017
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
1602015
Deep edge-aware filters
L Xu, J Ren, Q Yan, R Liao, J Jia
International Conference on Machine Learning, 1669-1678, 2015
1442015
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
1302018
Learning Important Spatial Pooling Regions for Scene Classification
D Lin, C Lu, R Liao, J Jia
IEEE Computer Vision and Pattern Recognition, 2014
1142014
Upsnet: A unified panoptic segmentation network
Y Xiong, R Liao, H Zhao, R Hu, M Bai, E Yumer, R Urtasun
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
1072019
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
1062015
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
87*2017
Nervenet: Learning structured policy with graph neural networks
T Wang, R Liao, J Ba, S Fidler
International Conference on Learning Representations, 2018
802018
Lanczosnet: Multi-scale deep graph convolutional networks
R Liao, Z Zhao, R Urtasun, RS Zemel
International Conference on Learning Representations, 2019
762019
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
722017
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
662018
Learning deep parsimonious representations
R Liao, A Schwing, R Zemel, R Urtasun
Advances in Neural Information Processing Systems, 5076-5084, 2016
662016
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
632016
Efficient graph generation with graph recurrent attention networks
R Liao, Y Li, Y Song, S Wang, W Hamilton, DK Duvenaud, R Urtasun, ...
Advances in Neural Information Processing Systems, 4255-4265, 2019
422019
Understanding short-horizon bias in stochastic meta-optimization
Y Wu, M Ren, R Liao, R Grosse
International Conference on Learning Representations, 2018
422018
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
402019
Incremental few-shot learning with attention attractor networks
M Ren, R Liao, E Fetaya, R Zemel
Advances in Neural Information Processing Systems 32, 5275-5285, 2019
382019
Graph partition neural networks for semi-supervised classification
R Liao, M Brockschmidt, D Tarlow, AL Gaunt, R Urtasun, R Zemel
International Conference on Learning Representations (Workshop Track), 2018
362018
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