| The light field camera: Extended depth of field, aliasing, and superresolution TE Bishop, P Favaro IEEE Transactions on Pattern Analysis and Machine Intelligence 34 (5), 972-986, 2012 | 458 | 2012 |
| Light field superresolution TE Bishop, S Zanetti, P Favaro Computational Photography (ICCP), 2009 IEEE International Conference on, 1-9, 2009 | 334 | 2009 |
| Multiview active shape models with SIFT descriptors for the 300-W face landmark challenge S Milborrow, T Bishop, F Nicolls Proceedings of the IEEE International Conference on Computer Vision …, 2013 | 256 | 2013 |
| OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold M Yousef, TE Bishop Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 107 | 2020 |
| Full-resolution depth map estimation from an aliased plenoptic light field TE Bishop, P Favaro Asian Conference on Computer Vision, 186-200, 2010 | 82 | 2010 |
| Plenoptic depth estimation from multiple aliased views TE Bishop, P Favaro Computer Vision Workshops (ICCV Workshops), 2009 IEEE 12th International …, 2009 | 77 | 2009 |
| Blind image deconvolution: problem formulation and existing approaches TE Bishop, SD Babacan, B Amizic, AK Katsaggelos, T Chan, R Molina Blind image deconvolution: Theory and Applications, 1-41, 2007 | 73* | 2007 |
| Lens-to-lens bokeh effect transformation. NTIRE 2023 challenge report MV Conde, M Kolmet, T Seizinger, TE Bishop, R Timofte Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 20 | 2023 |
| Blind restoration of blurred photographs via AR modelling and MCMC TE Bishop, R Molina, JR Hopgood 2008 15th IEEE International Conference on Image Processing, 669-672, 2008 | 14 | 2008 |
| Blind image restoration using a block-stationary signal model TE Bishop, JR Hopgood 2006 IEEE International Conference on Acoustics Speech and Signal Processing …, 2006 | 14 | 2006 |
| A Bayesian approach to shape from coded aperture M Martinello, TE Bishop, P Favaro 2010 IEEE International Conference on Image Processing, 3521-3524, 2010 | 13 | 2010 |
| Nonstationary Blind Image Restoration using Variational Methods. TE Bishop, R Molina, JR Hopgood ICIP (1), 125-128, 2007 | 7 | 2007 |
| Local Bayesian image restoration using variational methods and Gamma-Normal distributions. J Mateos, TE Bishop, R Molina, AK Katsaggelos ICIP, 129-132, 2009 | 6 | 2009 |
| Learning by Hallucinating: Vision-Language Pre-training with Weak Supervision TJJ Wang, J Laaksonen, T Langer, H Arponen, TE Bishop Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 4 | 2023 |
| SHREWD: Semantic Hierarchy-based Relational Embeddings for Weakly-supervised Deep Hashing H Arponen, TE Bishop arXiv preprint arXiv:1908.05602, 2019 | 4 | 2019 |
| Blind image deconvolution: nonstationary Bayesian approaches to restoring blurred photos TE Bishop The University of Edinburgh, 2009 | 4 | 2009 |
| No Shifted Augmentations (NSA): compact distributions for robust self-supervised Anomaly Detection M Yousef, M Ackermann, U Kurup, T Bishop arXiv preprint arXiv:2203.10344, 2022 | 2 | 2022 |
| Blind Deconvolution T Bishop, P Favaro Computer Vision, 52-57, 2014 | 2* | 2014 |
| No Shifted Augmentations (NSA): strong baselines for self-supervised Anomaly Detection M Yousef, T Bishop, U Kurup | | 2021 |
| Learning to hash with semantic similarity metrics and empirical KL divergence H Arponen, TE Bishop arXiv preprint arXiv:2005.04917, 2020 | | 2020 |
Paolo FavaroProfessor of Computer Vision, University of BernEmail verificata su iam.unibe.ch