Sarah Parisot

According to our database, Sarah Parisot authored at least 46 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

CLAD: A realistic Continual Learning benchmark for Autonomous Driving.

Eli Verwimp, Kuo Yang, Sarah Parisot, Lanqing Hong, Steven McDonagh, Eduardo Pérez-Pellitero, Matthias De Lange, Tinne Tuytelaars

Neural Networks, April, 2023

Optimisation-Based Multi-Modal Semantic Image Editing.

Bowen Li, Yongxin Yang, Steven McDonagh, Shifeng Zhang, Petru-Daniel Tudosiu, Sarah Parisot

CoRR, 2023

Learning to Name Classes for Vision and Language Models.

Sarah Parisot, Yongxin Yang, Steven McDonagh

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

A Continual Learning Survey: Defying Forgetting in Classification Tasks.

Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Ales Leonardis, Gregory G. Slabaugh, Tinne Tuytelaars

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Long-tail Recognition via Compositional Knowledge Transfer.

Sarah Parisot, Pedro M. Esperança, Steven McDonagh, Tamas J. Madarasz, Yongxin Yang, Zhenguo Li

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Re-examining Distillation for Continual Object Detection.

Eli Verwimp, Kuo Yang, Sarah Parisot, Lanqing Hong, Steven McDonagh, Eduardo Pérez-Pellitero, Matthias De Lange, Tinne Tuytelaars

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

Content-Diverse Comparisons improve IQA.

William Thong, José Costa Pereira, Sarah Parisot, Ales Leonardis, Steven McDonagh

Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021

Learning Compositional Shape Priors for Few-Shot 3D Reconstruction.

Mateusz Michalkiewicz, Stavros Tsogkas, Sarah Parisot, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky

CoRR, 2021

2020

Probabilistic 3D Surface Reconstruction from Sparse MRI Information.

Katarína Tóthová, Sarah Parisot, Matthew C. H. Lee, Esther Puyol-Antón, Andrew P. King, Marc Pollefeys, Ender Konukoglu

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Low Light Video Enhancement Using Synthetic Data Produced with an Intermediate Domain Mapping.

Danai Triantafyllidou, Sean Moran, Steven McDonagh, Sarah Parisot, Gregory G. Slabaugh

Proceedings of the Computer Vision - ECCV 2020, 2020

Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors.

Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas, Mahsa Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky

Proceedings of the Computer Vision - ECCV 2020, 2020

Many-Shot from Low-Shot: Learning to Annotate Using Mixed Supervision for Object Detection.

Carlo Biffi, Steven McDonagh, Philip H. S. Torr, Ales Leonardis, Sarah Parisot

Proceedings of the Computer Vision - ECCV 2020, 2020

More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental Learning.

Yu Liu, Sarah Parisot, Gregory G. Slabaugh, Xu Jia, Ales Leonardis, Tinne Tuytelaars

Proceedings of the Computer Vision - ECCV 2020, 2020

DeepLPF: Deep Local Parametric Filters for Image Enhancement.

Sean Moran, Pierre Marza, Steven McDonagh, Sarah Parisot, Gregory G. Slabaugh

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Unsupervised Model Personalization While Preserving Privacy and Scalability: An Open Problem.

Matthias De Lange, Xu Jia, Sarah Parisot, Ales Leonardis, Gregory G. Slabaugh, Tinne Tuytelaars

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

A Multi-Hypothesis Approach to Color Constancy.

Daniel Hernández Juárez, Sarah Parisot, Benjamin Busam, Ales Leonardis, Gregory G. Slabaugh, Steven McDonagh

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

EHSOD: CAM-Guided End-to-End Hybrid-Supervised Object Detection with Cascade Refinement.

Linpu Fang, Hang Xu, Zhili Liu, Sarah Parisot, Zhenguo Li

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Continual learning: A comparative study on how to defy forgetting in classification tasks.

Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Ales Leonardis, Gregory G. Slabaugh, Tinne Tuytelaars

CoRR, 2019

2018

Metric learning with spectral graph convolutions on brain connectivity networks.

Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert

NeuroImage, 2018

Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex.

Salim Arslan, Sofia Ira Ktena, Antonios Makropoulos, Emma C. Robinson, Daniel Rueckert, Sarah Parisot

NeuroImage, 2018

Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease.

Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero, Ben Glocker, Daniel Rueckert

Medical Image Anal., 2018

Meta-Learning for Few-shot Camera-Adaptive Color Constancy.

Steven McDonagh, Sarah Parisot, Zhenguo Li, Gregory G. Slabaugh

CoRR, 2018

Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer's Disease.

Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew Lee, Ricardo Guerrero, Ben Glocker, Daniel Rueckert

CoRR, 2018

Learning Conditioned Graph Structures for Interpretable Visual Question Answering.

Will Norcliffe-Brown, Stathis Vafeias, Sarah Parisot

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Uncertainty Quantification in CNN-Based Surface Prediction Using Shape Priors.

Katarína Tóthová, Sarah Parisot, Matthew C. H. Lee, Esther Puyol-Antón, Lisa M. Koch, Andrew P. King, Ender Konukoglu, Marc Pollefeys

Proceedings of the Shape in Medical Imaging, 2018

2017

A flexible graphical model for multi-modal parcellation of the cortex.

Sarah Parisot, Ben Glocker, Sofia Ira Ktena, Salim Arslan, Markus D. Schirmer, Daniel Rueckert

NeuroImage, 2017

Reproducible Large-Scale Neuroimaging Studies with the OpenMOLE Workflow Management System.

Jonathan Passerat-Palmbach, Romain Reuillon, Mathieu Leclaire, Antonios Makropoulos, Emma C. Robinson, Sarah Parisot, Daniel Rueckert

Frontiers Neuroinformatics, 2017

Spectral Graph Convolutions for Population-Based Disease Prediction.

Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero Moreno, Ben Glocker, Daniel Rueckert

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Distance Metric Learning Using Graph Convolutional Networks: Application to Functional Brain Networks.

Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Exploring heritability of functional brain networks with inexact graph matching.

Sofia Ira Ktena, Salim Arslan, Sarah Parisot, Daniel Rueckert

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

2016

Group-wise parcellation of the cortex through multi-scale spectral clustering.

Sarah Parisot, Salim Arslan, Jonathan Passerat-Palmbach, William M. Wells III, Daniel Rueckert

NeuroImage, 2016

(Hyper)-graphical models in biomedical image analysis.

Nikos Paragios, Enzo Ferrante, Ben Glocker, Nikos Komodakis, Sarah Parisot, Evangelia I. Zacharaki

Medical Image Anal., 2016

Proceedings of the Workshop on Brain Analysis using COnnectivity Networks - BACON 2016.

Sarah Parisot, Jonathan Passerat-Palmbach, Markus D. Schirmer, Boris Gutman

CoRR, 2016

Comparison of Brain Networks with Unknown Correspondences.

Sofia Ira Ktena, Sarah Parisot, Jonathan Passerat-Palmbach, Daniel Rueckert

CoRR, 2016

GraMPa: Graph-Based Multi-modal Parcellation of the Cortex Using Fusion Moves.

Sarah Parisot, Ben Glocker, Markus Schirmer, Daniel Rueckert

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

DeepMedic for Brain Tumor Segmentation.

Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya V. Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2016

Boundary Mapping Through Manifold Learning for Connectivity-Based Cortical Parcellation.

Salim Arslan, Sarah Parisot, Daniel Rueckert

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

2015

A Continuous Flow-Maximisation Approach to Connectivity-Driven Cortical Parcellation.

Sarah Parisot, Martin Rajchl, Jonathan Passerat-Palmbach, Daniel Rueckert

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015

Beyond the AHA 17-Segment Model: Motion-Driven Parcellation of the Left Ventricle.

Wenjia Bai, Devis Peressutti, Sarah Parisot, Ozan Oktay, Martin Rajchl, Declan P. O'Regan, Stuart A. Cook, Andrew P. King, Daniel Rueckert

Proceedings of the Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges, 2015

Tractography-Driven Groupwise Multi-scale Parcellation of the Cortex.

Sarah Parisot, Salim Arslan, Jonathan Passerat-Palmbach, William M. Wells III, Daniel Rueckert

Proceedings of the Information Processing in Medical Imaging, 2015

Joint Spectral Decomposition for the Parcellation of the Human Cerebral Cortex Using Resting-State fMRI.

Salim Arslan, Sarah Parisot, Daniel Rueckert

Proceedings of the Information Processing in Medical Imaging, 2015

2014

Concurrent tumor segmentation and registration with uncertainty-based sparse non-uniform graphs.

Sarah Parisot, William M. Wells III, Stéphane Chemouny, Hugues Duffau, Nikos Paragios

Medical Image Anal., 2014

2013

Uncertainty-Driven Efficiently-Sampled Sparse Graphical Models for Concurrent Tumor Segmentation and Atlas Registration.

Sarah Parisot, William M. Wells III, Stéphane Chemouny, Hugues Duffau, Nikos Paragios

Proceedings of the IEEE International Conference on Computer Vision, 2013

2012

Joint Tumor Segmentation and Dense Deformable Registration of Brain MR Images.

Sarah Parisot, Hugues Duffau, Stéphane Chemouny, Nikos Paragios

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012

Graph-based detection, segmentation & characterization of brain tumors.

Sarah Parisot, Hugues Duffau, Stéphane Chemouny, Nikos Paragios

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011

Graph Based Spatial Position Mapping of Low-Grade Gliomas.

Sarah Parisot, Hugues Duffau, Stéphane Chemouny, Nikos Paragios

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011, 2011