Seuraa
Renjie Liao
Renjie Liao
University of British Columbia
Vahvistettu sähköpostiosoite verkkotunnuksessa ece.ubc.ca - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
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
5112017
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
4942017
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
4122019
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
3402018
Learning lane graph representations for motion forecasting
M Liang, B Yang, R Hu, Y Chen, R Liao, S Feng, R Urtasun
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
3352020
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
2742015
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
2642019
Lanczosnet: Multi-scale deep graph convolutional networks
R Liao, Z Zhao, R Urtasun, RS Zemel
International Conference on Learning Representations, 2019
2372019
Deep edge-aware filters
L Xu, J Ren, Q Yan, R Liao, J Jia
International Conference on Machine Learning, 1669-1678, 2015
2332015
Nervenet: Learning structured policy with graph neural networks
T Wang, R Liao, J Ba, S Fidler
International Conference on Learning Representations, 2018
2322018
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
181*2020
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
1802019
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
1782017
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
1642018
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
1562015
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
1492017
Learning Important Spatial Pooling Regions for Scene Classification
D Lin, C Lu, R Liao, J Jia
IEEE Computer Vision and Pattern Recognition, 2014
1452014
Implicit latent variable model for scene-consistent motion forecasting
S Casas, C Gulino, S Suo, K Luo, R Liao, R Urtasun
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
1222020
Understanding short-horizon bias in stochastic meta-optimization
Y Wu, M Ren, R Liao, R Grosse
International Conference on Learning Representations, 2018
1182018
Darnet: Deep active ray network for building segmentation
D Cheng, R Liao, S Fidler, R Urtasun
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
1072019
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