Image Matching Across Wide Baselines: From Paper to Practice

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

In the context of automatic visual inspection of infrastructures by drones, Deep Learning (DL) models are used to automatically process images for fault diagnostics. While explainable Artificial Intelligence (AI) algorithms can provide explanations to asse ...

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

Chronic pain presents a tremendous personal, societal, and financial burden. Treatment options are often limited to managing symptoms as opposed to treating the causes, and the consequences of pharmacological treatments can be immensely harmful as evidence ...

Taking advantage of Capella's ability to dwell on a target for an extended period of time (nominally 30s) in its spotlight (SP) mode, an unsupervised methodology for detecting moving targets in this data is presented in this paper. By colourizing short seg ...

Modern machine learning (ML) models are capable of impressive performances. However, their prowess is not due only to the improvements in their architecture and training algorithms but also to a drastic increase in computational power used to train them.|S ...

Diffusion Magnetic Resonance Imaging (dMRI) is a powerful non-invasive method for studying white matter tracts of the brain. However, accurate microstructure estimation with fiber orientation distribution (FOD) using existing computational methods requires ...

Collaborative learning algorithms, such as distributed SGD (or D-SGD), are prone to faulty machines that may deviate from their prescribed algorithm because of software or hardware bugs, poisoned data or malicious behaviors. While many solutions have been ...

End-to-end learning methods like deep neural networks have been the driving force in the remarkable progress of machine learning in recent years. However, despite their success, the deployment process of such networks in safety-critical use cases, such as ...

Megapixel single-photon avalanche diode (SPAD) arrays have been developed recently, opening up the possibility of deploying SPADs as general-purpose passive cameras for photography and computer vision. However, most previous work on SPADs has been limited ...

Robustness of medical image classification models is limited by its exposure to the candidate disease classes. Generalized zero shot learning (GZSL) aims at correctly predicting seen and unseen classes and most current GZSL approaches have focused on the s ...

We consider the problem of compressing an information source when a correlated one is available as side information only at the decoder side, which is a special case of the distributed source coding problem in information theory. In particular, we consider ...

Despite the large body of academic work on machine learning security, little is known about the occurrence of attacks on machine learning systems in the wild. In this paper, we report on a quantitative study with 139 industrial practitioners. We analyze at ...

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

Over the years, clinical institutes accumulated large amounts of digital slides from resected tissue specimens. These digital images, called whole slide images (WSIs), are high-resolution tissue snapshots that depict the complex interaction of cells at the ...

In this thesis we present and analyze approximation algorithms for three different clustering problems. The formulations of these problems are motivated by fairness and explainability considerations, two issues that have recently received attention in the ...

The recent developments of deep learning cover a wide variety of tasks such as image classification, text translation, playing go, and folding proteins. All these successful methods depend on a gradient-based learning algorithm to train a model on massive ...

Cross-resolution face recognition has become a challenging problem for modern deep face recognition systems. It aims at matching a low-resolution probe image with high-resolution gallery images registered in a database. Existing methods mainly leverage pri ...

The Joint Photographic Experts Group (JPEG) AI learning-based image coding system is an ongoing joint standardization effort between International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), and International Te ...

Image Matching Across Wide Baselines: From Paper to Practice

Chat with Graph Search

Exploiting Explanations to Detect Misclassifications of Deep Learning Models in Power Grid Visual Inspection

Robust discrete choice models with t-distributed kernel errors

A Stand-Alone Augmented Reality Intervention for Chronic Pain using Embodied Systolic Stimulation

AN UNSUPERVISED METHOD FOR THE DETECTION OF AND TRACKING OF TARGETS IN SPOTLIGHT MODE SAR IMAGES

Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search

Robust Estimation of the Microstructure of the Early Developing Brain Using Deep Learning

Robust Collaborative Learning with Linear Gradient Overhead

Estimating and Improving the Robustness of Attributions in Text

Seeing Photons in Color

Class Specific Feature Disentanglement and Text Embeddings for Multi-label Generalized Zero Shot CXR Classification

Neural Distributed Image Compression with Cross-Attention Feature Alignment

Machine Learning Security in Industry: A Quantitative Survey

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Self-Supervised Learning for Patient Stratification and Survival Analysis in Computational Pathology: An Application to Colorectal Cancer

Fairness and Explainability in Clustering Problems

Transformer Models for Vision

Cross-resolution Face Recognition via Identity-Preserving Network and Knowledge Distillation

The JPEG AI Standard: Providing Efficient Human and Machine Visual Data Consumption