MRI k-space motion artefact augmentation: model robustness and task-specific uncertainty R Shaw, C Sudre, S Ourselin, MJ Cardoso | 59 | 2019 |
Human gaussian splatting: Real-time rendering of animatable avatars A Moreau, J Song, H Dhamo, R Shaw, Y Zhou, E Pérez-Pellitero Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 50 | 2024 |
A k-space model of movement artefacts: application to segmentation augmentation and artefact removal R Shaw, CH Sudre, T Varsavsky, S Ourselin, MJ Cardoso IEEE transactions on medical imaging 39 (9), 2881-2892, 2020 | 44 | 2020 |
NTIRE 2022 challenge on high dynamic range imaging: Methods and results E Pérez-Pellitero, S Catley-Chandar, R Shaw, A Leonardis, R Timofte, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 40 | 2022 |
Kä llberg, M., Cox, AJ, Kruglyak, S., and Saunders, CT (2016). Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications X Chen, O Schulz-Trieglaff, R Shaw, B Barnes, F Schlesinger Bioinformatics 32, 1220-1222, 0 | 30 | |
Headgas: Real-time animatable head avatars via 3d gaussian splatting H Dhamo, Y Nie, A Moreau, J Song, R Shaw, Y Zhou, E Pérez-Pellitero European Conference on Computer Vision, 459-476, 2024 | 23 | 2024 |
Neuromorphologicaly-preserving volumetric data encoding using VQ-VAE PD Tudosiu, T Varsavsky, R Shaw, M Graham, P Nachev, S Ourselin, ... arXiv preprint arXiv:2002.05692, 2020 | 21 | 2020 |
SWinGS: Sliding Windows for Dynamic 3D Gaussian Splatting R Shaw, M Nazarczuk, J Song, A Moreau, S Catley-Chandar, H Dhamo, ... arXiv preprint arXiv:2312.13308, 2023 | 14* | 2023 |
A multi-channel uncertainty-aware multi-resolution network for MR to CT synthesis K Klaser, P Borges, R Shaw, M Ranzini, M Modat, D Atkinson, ... Applied sciences 11 (4), 1667, 2021 | 13 | 2021 |
A heteroscedastic uncertainty model for decoupling sources of MRI image quality R Shaw, CH Sudre, S Ourselin, MJ Cardoso Medical Imaging with Deep Learning, 733-742, 2020 | 10 | 2020 |
Hdr reconstruction from bracketed exposures and events R Shaw, S Catley-Chandar, A Leonardis, E Perez-Pellitero arXiv preprint arXiv:2203.14825, 2022 | 8 | 2022 |
AIM 2024 sparse neural rendering challenge: Methods and results M Nazarczuk, S Catley-Chandar, T Tanay, R Shaw, E Pérez-Pellitero, ... arXiv preprint arXiv:2409.15045, 2024 | 7 | 2024 |
AIM 2024 sparse neural rendering challenge: Dataset and benchmark M Nazarczuk, T Tanay, S Catley-Chandar, R Shaw, R Timofte, ... arXiv preprint arXiv:2409.15041, 2024 | 7 | 2024 |
Data processing pipeline for Tianlai experiment S Zuo, J Li, Y Li, D Santanu, A Stebbins, KW Masui, R Shaw, J Zhang, ... Astronomy and Computing 34, 100439, 2021 | 7 | 2021 |
Acquisition-invariant brain MRI segmentation with informative uncertainties P Borges, R Shaw, T Varsavsky, K Kläser, D Thomas, I Drobnjak, ... Medical Image Analysis 92, 103058, 2024 | 6 | 2024 |
Vschh 2023: A benchmark for the view synthesis challenge of human heads Y Jang, J Zheng, J Song, H Dhamo, E Pérez-Pellitero, T Tanay, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 4 | 2023 |
A decoupled uncertainty model for mri segmentation quality estimation R Shaw, CH Sudre, S Ourselin, MJ Cardoso, HG Pemberton arXiv preprint arXiv:2109.02413, 2021 | 4 | 2021 |
Uncertainty-aware multi-resolution whole-body MR to CT synthesis K Kläser, P Borges, R Shaw, M Ranzini, M Modat, D Atkinson, ... Simulation and Synthesis in Medical Imaging: 5th International Workshop …, 2020 | 4 | 2020 |
RoGUENeRF: a robust geometry-consistent universal enhancer for NeRF S Catley-Chandar, R Shaw, G Slabaugh, E Pérez-Pellitero European Conference on Computer Vision, 54-71, 2024 | 3 | 2024 |
Kotekan: A framework for high-performance radiometric data pipelines A Renard, R Shaw, C Ng, R Nitsche, J Taylor, K Vanderlinde, K Masui, ... Zenodo, 2021 | 3 | 2021 |