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2020 – today
- 2024
[c30]Petru-Daniel Tudosiu, Yongxin Yang, Shifeng Zhang, Fei Chen, Steven McDonagh, Gerasimos Lampouras, Ignacio Iacobacci, Sarah Parisot:
MULAN: A Multi Layer Annotated Dataset for Controllable Text-to-Image Generation. CVPR 2024: 22413-22422- [i26]Petru-Daniel Tudosiu, Yongxin Yang, Shifeng Zhang, Fei Chen, Steven McDonagh, Gerasimos Lampouras, Ignacio Iacobacci, Sarah Parisot:
MULAN: A Multi Layer Annotated Dataset for Controllable Text-to-Image Generation. CoRR abs/2404.02790 (2024) - [i25]Danai Triantafyllidou, Sarah Parisot, Ales Leonardis, Steven McDonagh:
Improving Object Detection via Local-global Contrastive Learning. CoRR abs/2410.05058 (2024) - 2023
- [j10]Eli Verwimp
, Kuo Yang, Sarah Parisot, Lanqing Hong, Steven McDonagh, Eduardo Pérez-Pellitero, Matthias De Lange, Tinne Tuytelaars:
CLAD: A realistic Continual Learning benchmark for Autonomous Driving. Neural Networks 161: 659-669 (2023) - [c29]Sarah Parisot, Yongxin Yang, Steven McDonagh:
Learning to Name Classes for Vision and Language Models. CVPR 2023: 23477-23486 - [i24]Sarah Parisot, Yongxin Yang, Steven McDonagh:
Learning to Name Classes for Vision and Language Models. CoRR abs/2304.01830 (2023) - [i23]Bowen Li, Yongxin Yang, Steven McDonagh, Shifeng Zhang, Petru-Daniel Tudosiu, Sarah Parisot:
Optimisation-Based Multi-Modal Semantic Image Editing. CoRR abs/2311.16882 (2023) - 2022
- [j9]Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Ales Leonardis, Gregory G. Slabaugh, Tinne Tuytelaars:
A Continual Learning Survey: Defying Forgetting in Classification Tasks. IEEE Trans. Pattern Anal. Mach. Intell. 44(7): 3366-3385 (2022) - [c28]William Thong, José Costa Pereira, Sarah Parisot, Ales Leonardis, Steven McDonagh:
Content-Diverse Comparisons improve IQA. BMVC 2022: 244 - [c27]Eli Verwimp, Kuo Yang, Sarah Parisot, Lanqing Hong, Steven McDonagh, Eduardo Pérez-Pellitero, Matthias De Lange, Tinne Tuytelaars:
Re-examining Distillation for Continual Object Detection. BMVC 2022: 807 - [c26]Sarah Parisot, Pedro M. Esperança, Steven McDonagh, Tamas J. Madarasz, Yongxin Yang, Zhenguo Li:
Long-tail Recognition via Compositional Knowledge Transfer. CVPR 2022: 6929-6938 - [i22]Eli Verwimp, Kuo Yang, Sarah Parisot, Lanqing Hong, Steven McDonagh, Eduardo Pérez-Pellitero, Matthias De Lange, Tinne Tuytelaars:
Re-examining Distillation For Continual Object Detection. CoRR abs/2204.01407 (2022) - [i21]Eli Verwimp, Kuo Yang, Sarah Parisot, Lanqing Hong, Steven McDonagh, Eduardo Pérez-Pellitero, Matthias De Lange, Tinne Tuytelaars:
CLAD: A realistic Continual Learning benchmark for Autonomous Driving. CoRR abs/2210.03482 (2022) - [i20]William Thong, José Costa Pereira, Sarah Parisot, Ales Leonardis, Steven McDonagh:
Content-Diverse Comparisons improve IQA. CoRR abs/2211.05215 (2022) - 2021
- [i19]Mateusz Michalkiewicz, Stavros Tsogkas, Sarah Parisot, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky:
Learning Compositional Shape Priors for Few-Shot 3D Reconstruction. CoRR abs/2106.06440 (2021) - [i18]Sarah Parisot, Pedro M. Esperança, Steven McDonagh, Tamas J. Madarasz, Yongxin Yang, Zhenguo Li:
Long-tail Recognition via Compositional Knowledge Transfer. CoRR abs/2112.06741 (2021) - 2020
- [c25]Linpu Fang, Hang Xu, Zhili Liu, Sarah Parisot, Zhenguo Li:
EHSOD: CAM-Guided End-to-End Hybrid-Supervised Object Detection with Cascade Refinement. AAAI 2020: 10778-10785 - [c24]Daniel Hernández Juárez, Sarah Parisot, Benjamin Busam, Ales Leonardis, Gregory G. Slabaugh, Steven McDonagh:
A Multi-Hypothesis Approach to Color Constancy. CVPR 2020: 2267-2277 - [c23]Sean Moran, Pierre Marza, Steven McDonagh, Sarah Parisot, Gregory G. Slabaugh:
DeepLPF: Deep Local Parametric Filters for Image Enhancement. CVPR 2020: 12823-12832 - [c22]Matthias De Lange, Xu Jia, Sarah Parisot, Ales Leonardis, Gregory G. Slabaugh, Tinne Tuytelaars:
Unsupervised Model Personalization While Preserving Privacy and Scalability: An Open Problem. CVPR 2020: 14451-14460 - [c21]Carlo Biffi, Steven McDonagh, Philip H. S. Torr, Ales Leonardis, Sarah Parisot:
Many-Shot from Low-Shot: Learning to Annotate Using Mixed Supervision for Object Detection. ECCV (8) 2020: 35-50 - [c20]Danai Triantafyllidou, Sean Moran, Steven McDonagh, Sarah Parisot, Gregory G. Slabaugh:
Low Light Video Enhancement Using Synthetic Data Produced with an Intermediate Domain Mapping. ECCV (13) 2020: 103-119 - [c19]Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky:
Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors. ECCV (25) 2020: 614-630 - [c18]Yu Liu, Sarah Parisot, Gregory G. Slabaugh, Xu Jia, Ales Leonardis, Tinne Tuytelaars:
More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental Learning. ECCV (26) 2020: 699-716 - [c17]Katarína Tóthová, Sarah Parisot, Matthew C. H. Lee, Esther Puyol-Antón, Andrew P. King, Marc Pollefeys, Ender Konukoglu:
Probabilistic 3D Surface Reconstruction from Sparse MRI Information. MICCAI (1) 2020: 813-823 - [e3]Carole H. Sudre, Hamid Fehri, Tal Arbel, Christian F. Baumgartner, Adrian V. Dalca, Ryutaro Tanno, Koen Van Leemput, William M. Wells III, Aristeidis Sotiras, Bartlomiej W. Papiez, Enzo Ferrante, Sarah Parisot:
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis - Second International Workshop, UNSURE 2020, and Third International Workshop, GRAIL 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings. Lecture Notes in Computer Science 12443, Springer 2020, ISBN 978-3-030-60364-9 [contents] - [i17]Linpu Fang, Hang Xu, Zhili Liu, Sarah Parisot, Zhenguo Li:
EHSOD: CAM-Guided End-to-end Hybrid-Supervised Object Detection with Cascade Refinement. CoRR abs/2002.07421 (2020) - [i16]Daniel Hernández Juárez, Sarah Parisot, Benjamin Busam, Ales Leonardis, Gregory G. Slabaugh, Steven McDonagh:
A Multi-Hypothesis Approach to Color Constancy. CoRR abs/2002.12896 (2020) - [i15]Matthias De Lange, Xu Jia, Sarah Parisot, Ales Leonardis, Gregory G. Slabaugh, Tinne Tuytelaars:
Unsupervised Model Personalization while Preserving Privacy and Scalability: An Open Problem. CoRR abs/2003.13296 (2020) - [i14]Sean Moran, Pierre Marza, Steven McDonagh, Sarah Parisot, Gregory G. Slabaugh:
DeepLPF: Deep Local Parametric Filters for Image Enhancement. CoRR abs/2003.13985 (2020) - [i13]Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky:
Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors. CoRR abs/2004.06302 (2020) - [i12]Carlo Biffi, Steven McDonagh, Philip H. S. Torr, Ales Leonardis, Sarah Parisot:
Many-shot from Low-shot: Learning to Annotate using Mixed Supervision for Object Detection. CoRR abs/2008.09694 (2020) - [i11]Katarína Tóthová, Sarah Parisot, Matthew C. H. Lee, Esther Puyol-Antón, Andrew P. King, Marc Pollefeys, Ender Konukoglu:
Probabilistic 3D surface reconstruction from sparse MRI information. CoRR abs/2010.02041 (2020)
2010 – 2019
- 2019
- [i10]Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Ales Leonardis, Gregory G. Slabaugh, Tinne Tuytelaars:
Continual learning: A comparative study on how to defy forgetting in classification tasks. CoRR abs/1909.08383 (2019) - 2018
- [j8]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero, Ben Glocker, Daniel Rueckert:
Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease. Medical Image Anal. 48: 117-130 (2018) - [j7]Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert:
Metric learning with spectral graph convolutions on brain connectivity networks. NeuroImage 169: 431-442 (2018) - [j6]Salim Arslan, Sofia Ira Ktena, Antonios Makropoulos, Emma C. Robinson, Daniel Rueckert, Sarah Parisot:
Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex. NeuroImage 170: 5-30 (2018) - [c16]Katarína Tóthová, Sarah Parisot, Matthew C. H. Lee, Esther Puyol-Antón, Lisa M. Koch, Andrew P. King, Ender Konukoglu, Marc Pollefeys:
Uncertainty Quantification in CNN-Based Surface Prediction Using Shape Priors. ShapeMI@MICCAI 2018: 300-310 - [c15]Will Norcliffe-Brown, Stathis Vafeias, Sarah Parisot:
Learning Conditioned Graph Structures for Interpretable Visual Question Answering. NeurIPS 2018: 8344-8353 - [e2]Danail Stoyanov, Zeike Taylor, Enzo Ferrante, Adrian V. Dalca, Anne L. Martel, Lena Maier-Hein, Sarah Parisot, Aristeidis Sotiras, Bartlomiej W. Papiez, Mert R. Sabuncu, Li Shen:
Graphs in Biomedical Image Analysis - and - Integrating Medical Imaging and Non-Imaging Modalities - Second International Workshop, GRAIL 2018 - and - First International Workshop, Beyond MIC 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings. Lecture Notes in Computer Science 11044, Springer 2018, ISBN 978-3-030-00688-4 [contents] - [i9]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew Lee, Ricardo Guerrero, Ben Glocker, Daniel Rueckert:
Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer's Disease. CoRR abs/1806.01738 (2018) - [i8]Will Norcliffe-Brown, Efstathios Vafeias, Sarah Parisot:
Learning Conditioned Graph Structures for Interpretable Visual Question Answering. CoRR abs/1806.07243 (2018) - [i7]Katarína Tóthová, Sarah Parisot, Matthew C. H. Lee, Esther Puyol-Antón, Lisa M. Koch, Andrew P. King, Ender Konukoglu, Marc Pollefeys:
Uncertainty Quantification in CNN-Based Surface Prediction Using Shape Priors. CoRR abs/1807.11272 (2018) - [i6]Steven McDonagh, Sarah Parisot, Zhenguo Li, Gregory G. Slabaugh:
Meta-Learning for Few-shot Camera-Adaptive Color Constancy. CoRR abs/1811.11788 (2018) - 2017
- [j5]Jonathan Passerat-Palmbach, Romain Reuillon, Mathieu Leclaire, Antonios Makropoulos, Emma C. Robinson, Sarah Parisot, Daniel Rueckert:
Reproducible Large-Scale Neuroimaging Studies with the OpenMOLE Workflow Management System. Frontiers Neuroinformatics 11: 21 (2017) - [j4]Sarah Parisot, Ben Glocker, Sofia Ira Ktena, Salim Arslan, Markus D. Schirmer, Daniel Rueckert:
A flexible graphical model for multi-modal parcellation of the cortex. NeuroImage 162: 226-248 (2017) - [c14]Sofia Ira Ktena, Salim Arslan, Sarah Parisot, Daniel Rueckert:
Exploring heritability of functional brain networks with inexact graph matching. ISBI 2017: 354-357 - [c13]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero Moreno, Ben Glocker, Daniel Rueckert:
Spectral Graph Convolutions for Population-Based Disease Prediction. MICCAI (3) 2017: 177-185 - [c12]Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert:
Distance Metric Learning Using Graph Convolutional Networks: Application to Functional Brain Networks. MICCAI (1) 2017: 469-477 - [e1]M. Jorge Cardoso, Tal Arbel, Enzo Ferrante, Xavier Pennec, Adrian V. Dalca, Sarah Parisot, Sarang C. Joshi, Nematollah Kayhan Batmanghelich, Aristeidis Sotiras, Mads Nielsen, Mert R. Sabuncu, Tom Fletcher, Li Shen, Stanley Durrleman, Stefan Sommer:
Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - First International Workshop, GRAIL 2017, 6th International Workshop, MFCA 2017, and Third International Workshop, MICGen 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10-14, 2017, Proceedings. Lecture Notes in Computer Science 10551, Springer 2017, ISBN 978-3-319-67674-6 [contents] - [i5]Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert:
Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks. CoRR abs/1703.02161 (2017) - [i4]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero Moreno, Ben Glocker, Daniel Rueckert:
Spectral Graph Convolutions for Population-based Disease Prediction. CoRR abs/1703.03020 (2017) - [i3]Sofia Ira Ktena, Salim Arslan, Sarah Parisot, Daniel Rueckert:
Exploring Heritability of Functional Brain Networks with Inexact Graph Matching. CoRR abs/1703.10062 (2017) - 2016
- [j3]Nikos Paragios, Enzo Ferrante, Ben Glocker, Nikos Komodakis, Sarah Parisot, Evangelia I. Zacharaki:
(Hyper)-graphical models in biomedical image analysis. Medical Image Anal. 33: 102-106 (2016) - [j2]Sarah Parisot, Salim Arslan, Jonathan Passerat-Palmbach, William M. Wells III, Daniel Rueckert:
Group-wise parcellation of the cortex through multi-scale spectral clustering. NeuroImage 136: 68-83 (2016) - [c11]Salim Arslan, Sarah Parisot, Daniel Rueckert:
Boundary Mapping Through Manifold Learning for Connectivity-Based Cortical Parcellation. MICCAI (1) 2016: 115-122 - [c10]Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya V. Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker:
DeepMedic for Brain Tumor Segmentation. BrainLes@MICCAI 2016: 138-149 - [c9]Sarah Parisot, Ben Glocker, Markus Schirmer, Daniel Rueckert:
GraMPa: Graph-Based Multi-modal Parcellation of the Cortex Using Fusion Moves. MICCAI (1) 2016: 148-156 - [i2]Sarah Parisot, Jonathan Passerat-Palmbach, Markus D. Schirmer, Boris Gutman:
Proceedings of the Workshop on Brain Analysis using COnnectivity Networks - BACON 2016. CoRR abs/1611.03363 (2016) - [i1]Sofia Ira Ktena, Sarah Parisot, Jonathan Passerat-Palmbach, Daniel Rueckert:
Comparison of Brain Networks with Unknown Correspondences. CoRR abs/1611.04783 (2016) - 2015
- [c8]Salim Arslan, Sarah Parisot, Daniel Rueckert:
Joint Spectral Decomposition for the Parcellation of the Human Cerebral Cortex Using Resting-State fMRI. IPMI 2015: 85-97 - [c7]Sarah Parisot, Salim Arslan, Jonathan Passerat-Palmbach, William M. Wells III, Daniel Rueckert:
Tractography-Driven Groupwise Multi-scale Parcellation of the Cortex. IPMI 2015: 600-612 - [c6]Wenjia Bai, Devis Peressutti, Sarah Parisot, Ozan Oktay, Martin Rajchl, Declan P. O'Regan, Stuart A. Cook, Andrew P. King, Daniel Rueckert:
Beyond the AHA 17-Segment Model: Motion-Driven Parcellation of the Left Ventricle. STACOM@MICCAI 2015: 13-20 - [c5]Sarah Parisot, Martin Rajchl, Jonathan Passerat-Palmbach, Daniel Rueckert:
A Continuous Flow-Maximisation Approach to Connectivity-Driven Cortical Parcellation. MICCAI (3) 2015: 165-172 - 2014
- [j1]Sarah Parisot, William M. Wells III, Stéphane Chemouny, Hugues Duffau, Nikos Paragios:
Concurrent tumor segmentation and registration with uncertainty-based sparse non-uniform graphs. Medical Image Anal. 18(4): 647-659 (2014) - 2013
- [c4]Sarah Parisot, William M. Wells III, Stéphane Chemouny, Hugues Duffau, Nikos Paragios:
Uncertainty-Driven Efficiently-Sampled Sparse Graphical Models for Concurrent Tumor Segmentation and Atlas Registration. ICCV 2013: 641-648 - 2012
- [c3]Sarah Parisot, Hugues Duffau, Stéphane Chemouny, Nikos Paragios:
Graph-based detection, segmentation & characterization of brain tumors. CVPR 2012: 988-995 - [c2]Sarah Parisot, Hugues Duffau, Stéphane Chemouny, Nikos Paragios:
Joint Tumor Segmentation and Dense Deformable Registration of Brain MR Images. MICCAI (2) 2012: 651-658 - 2011
- [c1]Sarah Parisot, Hugues Duffau, Stéphane Chemouny, Nikos Paragios:
Graph Based Spatial Position Mapping of Low-Grade Gliomas. MICCAI (2) 2011: 508-515
Coauthor Index
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