126 citations · 426 across the 16 of their papers we have counts for
19 papers
Beyond Point Estimates for Glaucoma Visual Field Forecasting with Diffusion Models
Marta Colmenar Herrera, Pablo Márquez Neila, Şerife Seda Kucur Ergünay +2
Forecasting visual fields (VFs) is critical for personalized monitoring and treatment planning in glaucoma. This is inherently uncertain due to heterogeneous disease progression an…
Inferring geometry and material properties from Mueller matrices with machine learning
Lars Doorenbos, C. H. Lucas Patty, Raphael Sznitman +1
Mueller matrices (MMs) encode information on geometry and material properties, but recovering both simultaneously is an ill-posed problem. We explore whether MMs contain sufficient…
Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation
Fei Wu, Pablo Marquez-Neila, Hedyeh Rafi-Tarii +1
Multi-class semantic segmentation remains a cornerstone challenge in computer vision. Yet, dataset creation remains excessively demanding in time and effort, especially for special…
Online 3D reconstruction and dense tracking in endoscopic videos
Michel Hayoz, Christopher Hahne, Thomas Kurmann +5
3D scene reconstruction from stereo endoscopic video data is crucial for advancing surgical interventions. In this work, we present an online framework for online, dense 3D scene r…
Correlation-aware active learning for surgery video segmentation
Fei Wu, Pablo Marquez-Neila, Mingyi Zheng +2
Semantic segmentation is a complex task that relies heavily on large amounts of annotated image data. However, annotating such data can be time-consuming and resource-intensive, es…
Domain Adaptation for Medical Image Segmentation using Transformation-Invariant Self-Training
Negin Ghamsarian, Javier Gamazo Tejero, Pablo Márquez Neila +4
Models capable of leveraging unlabelled data are crucial in overcoming large distribution gaps between the acquired datasets across different imaging devices and configurations. In…
CataNet: Predicting remaining cataract surgery duration
Andrés Marafioti, Michel Hayoz, Mathias Gallardo +4
Cataract surgery is a sight saving surgery that is performed over 10 million times each year around the world. With such a large demand, the ability to organize surgical wards and…
Real-Time Camera Pose Estimation for Sports Fields
Leonardo Citraro, Pablo Márquez-Neila, Stefano Savarè +6
Given an image sequence featuring a portion of a sports field filmed by a moving and uncalibrated camera, such as the one of the smartphones, our goal is to compute automatically i…
Supervised Machine Learning for Intercomparison of Model Grids of Brown Dwarfs: Application to GJ 570D and the Epsilon Indi B Binary System
Maria Oreshenko, Daniel Kitzmann, Pablo Marquez-Neila +6
Self-consistent model grids of brown dwarfs involve complex physics and chemistry, and are often computed using proprietary computer codes, making it challenging to identify the re…
Fused Detection of Retinal Biomarkers in OCT Volumes
Thomas Kurmann, Pablo Márquez-Neila, Siqing Yu +3
Optical Coherence Tomography (OCT) is the primary imaging modality for detecting pathological biomarkers associated to retinal diseases such as Age-Related Macular Degeneration. In…
Deep Multi Label Classification in Affine Subspaces
Thomas Kurmann, Pablo Marquez Neila, Sebastian Wolf +1
Multi-label classification (MLC) problems are becoming increasingly popular in the context of medical imaging. This has in part been driven by the fact that acquiring annotations f…
Simulation of hyperelastic materials in real-time using Deep Learning
Andrea Mendizabal, Pablo Márquez-Neila, Stéphane Cotin
The finite element method (FEM) is among the most commonly used numerical methods for solving engineering problems. Due to its computational cost, various ideas have been introduce…
Self-Binarizing Networks
Fayez Lahoud, Radhakrishna Achanta, Pablo Márquez-Neila +1
We present a method to train self-binarizing neural networks, that is, networks that evolve their weights and activations during training to become binary. To obtain similar binary…
Supervised Machine Learning for Analysing Spectra of Exoplanetary Atmospheres
Pablo Marquez-Neila, Chloe Fisher, Raphael Sznitman +1
The use of machine learning is becoming ubiquitous in astronomy, but remains rare in the study of the atmospheres of exoplanets. Given the spectrum of an exoplanetary atmosphere, a…
Beyond the Pixel-Wise Loss for Topology-Aware Delineation
Agata Mosinska, Pablo Marquez-Neila, Mateusz Kozinski +1
Delineation of curvilinear structures is an important problem in Computer Vision with multiple practical applications. With the advent of Deep Learning, many current approaches on…
Simultaneous Recognition and Pose Estimation of Instruments in Minimally Invasive Surgery
Thomas Kurmann, Pablo Marquez Neila, Xiaofei Du +4
Detection of surgical instruments plays a key role in ensuring patient safety in minimally invasive surgery. In this paper, we present a novel method for 2D vision-based recognitio…
Imposing Hard Constraints on Deep Networks: Promises and Limitations
Pablo Márquez-Neila, Mathieu Salzmann, Pascal Fua
Imposing constraints on the output of a Deep Neural Net is one way to improve the quality of its predictions while loosening the requirements for labeled training data. Such constr…
Uniform Information Segmentation
Radhakrishna Achanta, Pablo Márquez-Neila, Pascal Fua +1
Size uniformity is one of the main criteria of superpixel methods. But size uniformity rarely conforms to the varying content of an image. The chosen size of the superpixels theref…
Learning to Fuse 2D and 3D Image Cues for Monocular Body Pose Estimation
Bugra Tekin, Pablo Márquez-Neila, Mathieu Salzmann +1
Most recent approaches to monocular 3D human pose estimation rely on Deep Learning. They typically involve regressing from an image to either 3D joint coordinates directly or 2D jo…