Aligning endoluminal scene sequences in wireless capsule endoscopy. - Michal Drozdzal; Laura Igual; Jordi Vitrià; Carolina Malagelada; Fernando Azpiroz; Petia Radeva (CVPR Workshops, 2010)

Interactive Labeling of WCE Images. - Michal Drozdzal; Santi Seguí; Carolina Malagelada; Fernando Azpiroz; Jordi Vitrià; Petia Radeva (IbPRIA, 2011)

Human Relative Position Detection Based on Mutual Occlusion. - Víctor Borjas; Michal Drozdzal; Petia Radeva; Jordi Vitrià (CIARP, 2012)

An Integrated Approach to Contextual Face Detection. - Santi Seguí; Michal Drozdzal; Petia Radeva; Jordi Vitrià (ICPRAM (2), 2012)

Active labeling: Application to wireless endoscopy analysis. - Petia Radeva; Michal Drozdzal; Santi Seguí; Laura Igual; Carolina Malagelada; Fernando Azpiroz; Jordi Vitrià (HPCS, 2012)

Categorization and Segmentation of Intestinal Content Frames for Wireless Capsule Endoscopy. - Santi Seguí; Michal Drozdzal; Fernando Vilariño; Carolina Malagelada; Fernando Azpiroz; Petia Radeva; Jordi Vitrià (IEEE Trans. Inf. Technol. Biomed., 2012)

A new image centrality descriptor for wrinkle frame detection in WCE videos. - Santi Seguí; Ekaterina Zaytseva; Michal Drozdzal; Carolina Malagelada; Fernando Azpiroz; Petia Radeva; Jordi Vitrià (MVA, 2013)

Adaptable image cuts for motility inspection using WCE. - Michal Drozdzal; Santi Seguí; Jordi Vitrià; Carolina Malagelada; Fernando Azpiroz; Petia Radeva (Comput. Medical Imaging Graph., 2013)

An Application for Efficient Error-Free Labeling of Medical Images. - Michal Drozdzal; Santi Seguí; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitrià (Multimodal Interaction in Image and Video Applications, 2013)

Intestinal event segmentation for endoluminal video analysis. - Michal Drozdzal; Jordi Vitrià; Santi Seguí; Carolina Malagelada; Fernando Azpiroz; Petia Radeva (ICIP, 2014)

Detection of Wrinkle Frames in Endoluminal Videos Using Betweenness Centrality Measures for Images. - Santi Seguí; Michal Drozdzal; Ekaterina Zaytseva; Carolina Malagelada; Fernando Azpiroz; Petia Radeva; Jordi Vitrià (IEEE J. Biomed. Health Informatics, 2014)

Motility bar: A new tool for motility analysis of endoluminal videos. - Michal Drozdzal; Santi Seguí; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitrià (Comput. Biol. Medicine, 2015)

Deep Learning Features for Wireless Capsule Endoscopy Analysis. - Santi Seguí; Michal Drozdzal; Guillem Pascual; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitrià (CIARP, 2016)

The Importance of Skip Connections in Biomedical Image Segmentation. - Michal Drozdzal; Eugene Vorontsov; Gabriel Chartrand; Samuel Kadoury; Chris Pal (LABELS/DLMIA@MICCAI, 2016)

Generic feature learning for wireless capsule endoscopy analysis. - Santi Seguí; Michal Drozdzal; Guillem Pascual; Petia Radeva; Carolina Malagelada; Fernando Azpiroz; Jordi Vitrià (Comput. Biol. Medicine, 2016)

A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images. - David Vázquez 001; Jorge Bernal; Francisco Javier Sánchez; Gloria Fernández-Esparrach; Antonio M. López 001; Adriana Romero; Michal Drozdzal; Aaron C. Courville (CoRR, 2016)

The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation. - Simon Jégou; Michal Drozdzal; David Vázquez 001; Adriana Romero; Yoshua Bengio (CVPR Workshops, 2017)

Learning Normalized Inputs for Iterative Estimation in Medical Image Segmentation. - Michal Drozdzal; Gabriel Chartrand; Eugene Vorontsov; Lisa Di-Jorio; An Tang; Adriana Romero; Yoshua Bengio; Chris Pal; Samuel Kadoury (CoRR, 2017)

Image Segmentation by Iterative Inference from Conditional Score Estimation. - Adriana Romero; Michal Drozdzal; Akram Erraqabi; Simon Jégou; Yoshua Bengio (CoRR, 2017)

Learnable Explicit Density for Continuous Latent Space and Variational Inference. - Chin-Wei Huang; Ahmed Touati; Laurent Dinh; Michal Drozdzal; Mohammad Havaei; Laurent Charlin; Aaron C. Courville (CoRR, 2017)

On the Iterative Refinement of Densely Connected Representation Levels for Semantic Segmentation. - Arantxa Casanova; Guillem Cucurull; Michal Drozdzal; Adriana Romero; Yoshua Bengio (CVPR Workshops, 2018)

fastMRI: An Open Dataset and Benchmarks for Accelerated MRI. - Jure Zbontar; Florian Knoll; Anuroop Sriram; Matthew J. Muckley; Mary Bruno; Aaron Defazio; Marc Parente; Krzysztof J. Geras; Joe Katsnelson; Hersh Chandarana; Zizhao Zhang; Michal Drozdzal; et al. (CoRR, 2018)

Learning normalized inputs for iterative estimation in medical image segmentation. - Michal Drozdzal; Gabriel Chartrand; Eugene Vorontsov; Mahsa Shakeri; Lisa Di-Jorio; An Tang; Adriana Romero; Yoshua Bengio; Chris Pal; Samuel Kadoury (Medical Image Anal., 2018)

Inverse Cooking: Recipe Generation From Food Images. - Amaia Salvador; Michal Drozdzal; Xavier Giró-i-Nieto; Adriana Romero (CVPR, 2019)

Reducing Uncertainty in Undersampled MRI Reconstruction With Active Acquisition. - Zizhao Zhang; Adriana Romero; Matthew J. Muckley; Pascal Vincent; Lin Yang 002; Michal Drozdzal (CVPR, 2019)

The Liver Tumor Segmentation Benchmark (LiTS). - Patrick Bilic; Patrick Ferdinand Christ; Eugene Vorontsov; Grzegorz Chlebus; Hao Chen 011; Qi Dou 001; Chi-Wing Fu; Xiao Han; Pheng-Ann Heng; Jürgen Hesser; Samuel Kadoury; Tomasz K. Konopczynski; et al. (CoRR, 2019)

Elucidating image-to-set prediction: An analysis of models, losses and datasets. - Luis Pineda; Amaia Salvador; Michal Drozdzal; Adriana Romero (CoRR, 2019)

On the Evaluation of Conditional GANs. - Terrance DeVries; Adriana Romero; Luis Pineda; Graham W. Taylor; Michal Drozdzal (CoRR, 2019)

Needles in Haystacks: On Classifying Tiny Objects in Large Images. - Nick Pawlowski; Suvrat Bhooshan; Nicolas Ballas; Francesco Ciompi; Ben Glocker; Michal Drozdzal (CoRR, 2019)

Active MR k-space Sampling with Reinforcement Learning. - Luis Pineda; Sumana Basu; Adriana Romero; Roberto Calandra; Michal Drozdzal (MICCAI (2), 2020)

Extending Unsupervised Neural Image Compression With Supervised Multitask Learning. - David Tellez; Diederik Höppener; Cornelis Verhoef; Dirk J. Grünhagen; Pieter Nierop; Michal Drozdzal; Jeroen van der Laak; Francesco Ciompi (MIDL, 2020)

Instance Selection for GANs. - Terrance DeVries; Michal Drozdzal; Graham W. Taylor (NeurIPS, 2020)

3D Shape Reconstruction from Vision and Touch. - Edward J. Smith; Roberto Calandra; Adriana Romero; Georgia Gkioxari; David Meger; Jitendra Malik; Michal Drozdzal (NeurIPS, 2020)

Generating unseen complex scenes: are we there yet? - Arantxa Casanova; Michal Drozdzal; Adriana Romero-Soriano (CoRR, 2020)

Instance-Conditioned GAN. - Arantxa Casanova; Marlène Careil; Jakob Verbeek; Michal Drozdzal; Adriana Romero-Soriano (NeurIPS, 2021)

Parameter Prediction for Unseen Deep Architectures. - Boris Knyazev 001; Michal Drozdzal; Graham W. Taylor; Adriana Romero-Soriano (NeurIPS, 2021)

Active 3D Shape Reconstruction from Vision and Touch. - Edward J. Smith; David Meger; Luis Pineda; Roberto Calandra; Jitendra Malik; Adriana Romero-Soriano; Michal Drozdzal (NeurIPS, 2021)

Active 3D Shape Reconstruction from Vision and Touch. - Edward J. Smith; David Meger; Luis Pineda; Roberto Calandra; Jitendra Malik; Adriana Romero; Michal Drozdzal (CoRR, 2021)

On learning adaptive acquisition policies for undersampled multi-coil MRI reconstruction. - Tim Bakker; Matthew J. Muckley; Adriana Romero-Soriano; Michal Drozdzal; Luis Pineda (MIDL, 2022)

Uncertainty-Driven Active Vision for Implicit Scene Reconstruction. - Edward J. Smith; Michal Drozdzal; Derek Nowrouzezahrai; David Meger; Adriana Romero-Soriano (CoRR, 2022)

ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. - Badr Youbi Idrissi; Diane Bouchacourt; Randall Balestriero; Ivan Evtimov; Caner Hazirbas; Nicolas Ballas; Pascal Vincent; Michal Drozdzal; David Lopez-Paz; Mark Ibrahim (ICLR, 2023)

Learning to Substitute Ingredients in Recipes. - Bahare Fatemi; Quentin Duval; Rohit Girdhar; Michal Drozdzal; Adriana Romero-Soriano (CoRR, 2023)

Instance-Conditioned GAN Data Augmentation for Representation Learning. - Pietro Astolfi; Arantxa Casanova; Jakob Verbeek; Pascal Vincent; Adriana Romero-Soriano; Michal Drozdzal (CoRR, 2023)

Controllable Image Generation via Collage Representations. - Arantxa Casanova; Marlène Careil; Adriana Romero-Soriano; Christopher J. Pal; Jakob Verbeek; Michal Drozdzal (CoRR, 2023)

The Liver Tumor Segmentation Benchmark (LiTS). - Patrick Bilic; Patrick Ferdinand Christ; Hongwei Li 004; Eugene Vorontsov; Avi Ben-Cohen; Georgios Kaissis; Adi Szeskin; Colin Jacobs; Gabriel Efrain Humpire Mamani; Gabriel Chartrand; Fabian Lohöfer; Julian Walter Holch; et al. (Medical Image Anal., 2023)

Improved baselines for vision-language pre-training. - Enrico Fini; Pietro Astolfi; Adriana Romero-Soriano; Jakob Verbeek; Michal Drozdzal (Trans. Mach. Learn. Res., 2023)

Improving Geo-Diversity of Generated Images with Contextualized Vendi Score Guidance. - Reyhane Askari Hemmat; Melissa Hall; Alicia Sun; Candace Ross; Michal Drozdzal; Adriana Romero-Soriano (ECCV (87), 2024)

Towards Geographic Inclusion in the Evaluation of Text-to-Image Models. - Melissa Hall; Samuel J. Bell; Candace Ross; Adina Williams; Michal Drozdzal; Adriana Romero-Soriano (FAccT, 2024)

On improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models. - Tariq Berrada Ifriqi; Pietro Astolfi; Melissa Hall; Reyhane Askari Hemmat; Yohann Benchetrit; Marton Havasi; Matthew J. Muckley; Karteek Alahari; Adriana Romero-Soriano; Jakob Verbeek; Michal Drozdzal (NeurIPS, 2024)

InCoRo: In-Context Learning for Robotics Control with Feedback Loops. - Jiaqiang Ye Zhu; Carla Gomez Cano; David Vázquez Bermudez; Michal Drozdzal (CoRR, 2024)

Consistency-diversity-realism Pareto fronts of conditional image generative models. - Pietro Astolfi; Marlène Careil; Melissa Hall; Oscar Mañas; Matthew J. Muckley; Jakob Verbeek; Adriana Romero-Soriano; Michal Drozdzal (CoRR, 2024)

On Improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models. - Tariq Berrada; Pietro Astolfi; Melissa Hall; Reyhane Askari Hemmat; Yohann Benchetrit; Marton Havasi; Matthew J. Muckley; Karteek Alahari; Adriana Romero-Soriano; Jakob Verbeek; Michal Drozdzal (CoRR, 2024)

EvalGIM: A Library for Evaluating Generative Image Models. - Melissa Hall; Oscar Mañas; Reyhane Askari Hemmat; Mark Ibrahim; Candace Ross; Pietro Astolfi; Tariq Berrada Ifriqi; Marton Havasi; Yohann Benchetrit; Karen Ullrich; Carolina Braga; Abhishek Charnalia; et al. (CoRR, 2024)

DIG In: Evaluating Disparities in Image Generations with Indicators for Geographic Diversity. - Melissa Hall; Candace Ross; Adina Williams; Nicolas Carion; Michal Drozdzal; Adriana Romero-Soriano (Trans. Mach. Learn. Res., 2024)

Feedback-guided Data Synthesis for Imbalanced Classification. - Reyhane Askari Hemmat; Mohammad Pezeshki; Florian Bordes; Michal Drozdzal; Adriana Romero-Soriano (Trans. Mach. Learn. Res., 2024)

Improving Text-to-Image Consistency via Automatic Prompt Optimization. - Oscar Mañas; Pietro Astolfi; Melissa Hall; Candace Ross; Jack Urbanek; Adina Williams; Aishwarya Agrawal; Adriana Romero-Soriano; Michal Drozdzal (Trans. Mach. Learn. Res., 2024)

Boosting Latent Diffusion with Perceptual Objectives. - Tariq Berrada; Pietro Astolfi; Melissa Hall; Marton Havasi; Yohann Benchetrit; Adriana Romero-Soriano; Karteek Alahari; Michal Drozdzal; Jakob Verbeek (ICLR, 2025)

Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control. - Carles Domingo-Enrich; Michal Drozdzal; Brian Karrer; Ricky T. Q. Chen (ICLR, 2025)

Object-centric Binding in Contrastive Language-Image Pretraining. - Rim Assouel; Pietro Astolfi; Florian Bordes; Michal Drozdzal; Adriana Romero-Soriano (CoRR, 2025)

Improving the Scaling Laws of Synthetic Data with Deliberate Practice. - Reyhane Askari Hemmat; Mohammad Pezeshki; Elvis Dohmatob; Florian Bordes; Pietro Astolfi; Melissa Hall; Jakob Verbeek; Michal Drozdzal; Adriana Romero-Soriano (CoRR, 2025)

Entropy Rectifying Guidance for Diffusion and Flow Models. - Tariq Berrada Ifriqi; Adriana Romero-Soriano; Michal Drozdzal; Jakob Verbeek; Karteek Alahari (CoRR, 2025)

Multi-Modal Language Models as Text-to-Image Model Evaluators. - Jiahui Chen; Candace Ross; Reyhane Askari Hemmat; Koustuv Sinha; Melissa Hall; Michal Drozdzal; Adriana Romero-Soriano (CoRR, 2025)

Increasing the Utility of Synthetic Images through Chamfer Guidance. - Nicola Dall'Asen; Xiaofeng Zhang; Reyhane Askari Hemmat; Melissa Hall; Jakob Verbeek; Adriana Romero-Soriano; Michal Drozdzal (CoRR, 2025)

Controlling Multimodal LLMs via Reward-guided Decoding. - Oscar Mañas; Pierluca D'Oro; Koustuv Sinha; Adriana Romero-Soriano; Michal Drozdzal; Aishwarya Agrawal (CoRR, 2025)