Sarah Parisot

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 55

Top Topics

Tumor Segmentation

Cerebral Cortex

Metric Learning

Top Venues

Publications

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 (2024)
Sarah Parisot, Yongxin Yang, Steven McDonagh
Learning to Name Classes for Vision and Language Models. CoRR (2023)
Sarah Parisot, Yongxin Yang, Steven McDonagh
Learning to Name Classes for Vision and Language Models. CVPR (2023)
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 (2023)
Bowen Li, Yongxin Yang, Steven McDonagh, Shifeng Zhang, Petru-Daniel Tudosiu, Sarah Parisot
Optimisation-Based Multi-Modal Semantic Image Editing. CoRR (2023)
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 (2022)
William Thong, José Costa Pereira, Sarah Parisot, Ales Leonardis, Steven McDonagh
Content-Diverse Comparisons improve IQA. BMVC (2022)
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 (2022)
Sarah Parisot, Pedro M. Esperança, Steven McDonagh, Tamas J. Madarasz, Yongxin Yang, Zhenguo Li
Long-tail Recognition via Compositional Knowledge Transfer. CVPR (2022)
William Thong, José Costa Pereira, Sarah Parisot, Ales Leonardis, Steven McDonagh
Content-Diverse Comparisons improve IQA. CoRR (2022)
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)
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) (2022)
Sarah Parisot, Pedro M. Esperança, Steven McDonagh, Tamas J. Madarasz, Yongxin Yang, Zhenguo Li
Long-tail Recognition via Compositional Knowledge Transfer. CoRR (2021)
Mateusz Michalkiewicz, Stavros Tsogkas, Sarah Parisot, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky
Learning Compositional Shape Priors for Few-Shot 3D Reconstruction. CoRR (2021)
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)
Daniel Hernández Juárez, Sarah Parisot, Benjamin Busam, Ales Leonardis, Gregory G. Slabaugh, Steven McDonagh
A Multi-Hypothesis Approach to Color Constancy. CoRR (2020)
Linpu Fang, Hang Xu, Zhili Liu, Sarah Parisot, Zhenguo Li
EHSOD: CAM-Guided End-to-end Hybrid-Supervised Object Detection with Cascade Refinement. CoRR (2020)
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 (2020)
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 (2020)
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 (2020)
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)
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)
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)
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)
Sean Moran, Pierre Marza, Steven McDonagh, Sarah Parisot, Gregory G. Slabaugh
DeepLPF: Deep Local Parametric Filters for Image Enhancement. CoRR (2020)
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 (2020)
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)
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)
Daniel Hernández Juárez, Sarah Parisot, Benjamin Busam, Ales Leonardis, Gregory G. Slabaugh, Steven McDonagh
A Multi-Hypothesis Approach to Color Constancy. CVPR (2020)
Sean Moran, Pierre Marza, Steven McDonagh, Sarah Parisot, Gregory G. Slabaugh
DeepLPF: Deep Local Parametric Filters for Image Enhancement. CVPR (2020)
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 (2019)
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 (2018)
Will Norcliffe-Brown, Efstathios Vafeias, Sarah Parisot
Learning Conditioned Graph Structures for Interpretable Visual Question Answering. CoRR (2018)
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 (2018)
Will Norcliffe-Brown, Stathis Vafeias, Sarah Parisot
Learning Conditioned Graph Structures for Interpretable Visual Question Answering. NeurIPS (2018)
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 (2018)
Steven McDonagh, Sarah Parisot, Zhenguo Li, Gregory G. Slabaugh
Meta-Learning for Few-shot Camera-Adaptive Color Constancy. CoRR (2018)
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 (2018)
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)
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 (2018)
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)
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 (2017)
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)
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 (2017)
Sofia Ira Ktena, Salim Arslan, Sarah Parisot, Daniel Rueckert
Exploring heritability of functional brain networks with inexact graph matching. ISBI (2017)
Sofia Ira Ktena, Salim Arslan, Sarah Parisot, Daniel Rueckert
Exploring Heritability of Functional Brain Networks with Inexact Graph Matching. CoRR (2017)
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 (2017)
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 (2017)
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)
Sarah Parisot, Jonathan Passerat-Palmbach, Markus D. Schirmer, Boris Gutman
Proceedings of the Workshop on Brain Analysis using COnnectivity Networks - BACON 2016. CoRR (2016)
Sarah Parisot, Ben Glocker, Markus Schirmer, Daniel Rueckert
GraMPa: Graph-Based Multi-modal Parcellation of the Cortex Using Fusion Moves. MICCAI (1) (2016)
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 (2016)
Sofia Ira Ktena, Sarah Parisot, Jonathan Passerat-Palmbach, Daniel Rueckert
Comparison of Brain Networks with Unknown Correspondences. CoRR (2016)
Nikos Paragios, Enzo Ferrante, Ben Glocker, Nikos Komodakis, Sarah Parisot, Evangelia I. Zacharaki
(Hyper)-graphical models in biomedical image analysis. Medical Image Anal. 33 (2016)
Salim Arslan, Sarah Parisot, Daniel Rueckert
Boundary Mapping Through Manifold Learning for Connectivity-Based Cortical Parcellation. MICCAI (1) (2016)
Salim Arslan, Sarah Parisot, Daniel Rueckert
Joint Spectral Decomposition for the Parcellation of the Human Cerebral Cortex Using Resting-State fMRI. IPMI (2015)
Sarah Parisot, Martin Rajchl, Jonathan Passerat-Palmbach, Daniel Rueckert
A Continuous Flow-Maximisation Approach to Connectivity-Driven Cortical Parcellation. MICCAI (3) (2015)
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)
Sarah Parisot, Salim Arslan, Jonathan Passerat-Palmbach, William M. Wells III, Daniel Rueckert
Tractography-Driven Groupwise Multi-scale Parcellation of the Cortex. IPMI (2015)
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) (2014)
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)
Sarah Parisot, Hugues Duffau, Stéphane Chemouny, Nikos Paragios
Joint Tumor Segmentation and Dense Deformable Registration of Brain MR Images. MICCAI (2) (2012)
Sarah Parisot, Hugues Duffau, Stéphane Chemouny, Nikos Paragios
Graph-based detection, segmentation & characterization of brain tumors. CVPR (2012)
Sarah Parisot, Hugues Duffau, Stéphane Chemouny, Nikos Paragios
Graph Based Spatial Position Mapping of Low-Grade Gliomas. MICCAI (2) (2011)