| Photo-realistic single image super-resolution using a generative adversarial network C Ledig, L Theis, F Huszár, J Caballero, A Cunningham, A Acosta, ... Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 8600 | 2017 |
| Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network W Shi, J Caballero, F Huszár, J Totz, AP Aitken, R Bishop, D Rueckert, ... Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 4140 | 2016 |
| Real-time video super-resolution with spatio-temporal networks and motion compensation J Caballero, C Ledig, A Aitken, A Acosta, J Totz, Z Wang, W Shi Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 535 | 2017 |
| Proceedings of the IEEE conference on computer vision and pattern recognition C Ledig, L Theis, F Huszár, J Caballero, A Cunningham, A Acosta, ... Photo-realistic single image super-resolution using a generative adversarial …, 2017 | 271 | 2017 |
| Checkerboard artifact free sub-pixel convolution: A note on sub-pixel convolution, resize convolution and convolution resize A Aitken, C Ledig, L Theis, J Caballero, Z Wang, W Shi arXiv preprint arXiv:1707.02937, 2017 | 139 | 2017 |
| Is the deconvolution layer the same as a convolutional layer? W Shi, J Caballero, L Theis, F Huszar, A Aitken, C Ledig, Z Wang arXiv preprint arXiv:1609.07009, 2016 | 135 | 2016 |
| Discriminative dictionary learning for abdominal multi-organ segmentation T Tong, R Wolz, Z Wang, Q Gao, K Misawa, M Fujiwara, K Mori, JV Hajnal, ... Medical image analysis 23 (1), 92-104, 2015 | 134 | 2015 |
| Geodesic Patch-based Segmentation Z Wang, K Bhatia, B Glocker, A de Marvao, T Dawes, K Misawa, K Mori, ... | 85 | 2014 |
| Enhancing visual data using and augmenting model libraries Z Wang, RD Bishop, W Shi, J Caballero, AP Aitken, J Totz US Patent 10,499,069, 2019 | 67 | 2019 |
| Training end-to-end video processes Z Wang, RD Bishop, F Huszar, L Theis US Patent 10,681,361, 2020 | 60 | 2020 |
| Machine Learning for Visual Processing Z Wang, RD Bishop, W Shi, J Caballero, AP Aitken, J Totz US Patent App. 15/679,984, 2017 | 49 | 2017 |
| Frame interpolation with multi-scale deep loss functions and generative adversarial networks J van Amersfoort, W Shi, A Acosta, F Massa, J Totz, Z Wang, J Caballero arXiv preprint arXiv:1711.06045, 2017 | 40 | 2017 |
| Patch-based segmentation without registration: application to knee MRI Z Wang, C Donoghue, D Rueckert International Workshop on Machine Learning in Medical Imaging, 98-105, 2013 | 31 | 2013 |
| Training end-to-end video processes Z Wang, RD Bishop, F Huszar, L Theis US Patent 10,666,962, 2020 | 25 | 2020 |
| Online Training of Hierarchical Algorithms Z Wang, RD Bishop, W Shi, J Caballero, AP Aitken, J Totz US Patent App. 15/679,660, 2017 | 24 | 2017 |
| Visual processing using temporal and spatial interpolation Z Wang, RD Bishop, W Shi, J Caballero, AP Aitken, J Totz US Patent 10,630,996, 2020 | 19 | 2020 |
| Enhancement of visual data Z Wang, RD Bishop, W Shi, J Caballero, AP Aitken, J Totz US Patent 10,523,955, 2019 | 16 | 2019 |
| Visual processing using sub-pixel convolutions Z Wang, RD Bishop, W Shi, J Caballero, AP Aitken, J Totz US Patent 10,887,613, 2021 | 14 | 2021 |
| Enhancing visual data using strided convolutions Z Wang, RD Bishop, W Shi, J Caballero, AP Aitken, J Totz US Patent 10,582,205, 2020 | 14 | 2020 |
| Accelerating machine optimisation processes Z Wang, RD Bishop, W Shi, J Caballero, AP Aitken, J Totz US Patent 10,516,890, 2019 | 14 | 2019 |
