Adversarial Confidence Estimation Networks for Robust Stereo Matching

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Current progress in artificial intelligence is centered around so-called large language models that consist of neural networks processing long sequences of high-dimensional vectors called tokens. Statistical physics provides powerful tools to study the fun ...

Since the 1960s, the prevalence of pollen allergy has increased worldwide in developed countries and this trend is continuing, exacerbated by climate change. In the 20th century, operational pollen monitoring networks have been set-up to respond to the nee ...

Pose-invariant face recognition has become a challenging problem for modern AI-based face recognition systems. It aims at matching a profile face captured in the wild with a frontal face registered in a database. Existing methods perform face frontalizatio ...

This thesis is concerned with improving the interpretability of network summaries in both a theoretical and an applied framework, with an application to clinically relevant problems in neuroscience. The theoretical part of this thesis is concerned with gra ...

Identification of spot-like structures in large, noisy microscopy images is a crucial step for many life-science applications. Imaging-based spatial transcriptomics (iST), in particular, relies on the precise detection of millions of transcripts in low sig ...

Holography enables quantitative phase sensing through light wave interference, allowing interesting imaging modalities applied in computational microscopy where phase shift is used as a way to generate image contrast. Recovering both amplitude and phase di ...

Background and Objective: Cardiovascular diseases, a leading cause of noncommunicable disease-related deaths, require early and accurate detection to improve patient outcomes. Taking advantage of advances in machine learning and deep learning, multiple app ...

The EPFL Graph Platform is an open-source data infrastructure designed for academic institutions. It organizes educational and institutional data into a semantically interconnected knowledge graph, making it accessible through a graph-based search engine a ...

Visual anomaly detection (AD) presents significant challenges due to the scarcity of anomalous data samples. While numerous works have been proposed to synthesize anomalous samples, these synthetic anomalies often lack authenticity or require extensive tra ...

The increasing accumulation of medical data brings the hope of data-driven medical decision-making, but data's increasing complexity—as text or images in electronic health records—calls for complex models, such as machine learning. Here, we review how mach ...

In recent decades, the rapid growth of cloud computing has transformed the technological landscape and profoundly impacted our daily lives, driven by the demand for secure, flexible, and cost-effective computing solutions. To meet these demands, computing ...

Cross-view localization, the task of estimating a camera's 3-degrees-of-freedom (3-DoF) pose by aligning ground-level images with satellite images, is crucial for large-scale outdoor applications like autonomous navigation and augmented reality. Existing m ...

Recent studies show that a reproducing kernel Hilbert space (RKHS) is not a suitable space to model functions by neural networks as the curse of dimensionality (CoD) cannot be evaded when trying to approximate even a single ReLU neuron (Bach, 2017). In thi ...

Project-based learning (PBL), as one of the effective teaching and learning approaches in engineering education, can create opportunities for students to address problems with real-world applications, integrate and apply knowledge, and practice and develop ...

Reasoning about distance is indispensable for establishing or avoiding contact in manipulation tasks. To this end, we present an online approach for learning implicit representations of signed distance using piecewise polynomial basis functions. Starting f ...

Deep convolutional neural networks (DCNNs) have significantly advanced the field of computer vision and are often considered as plausible models for the human visual system. However, they still have several vulnerabilities in terms of adversarial attacks, ...

With the significant increase in photovoltaic (PV) electricity generation, more attention has been given to PV power forecasting. Indeed, accurate forecasting allows power grid operators to better schedule and dispatch their assets, such as energy storage ...

Recent advances in deep learning and Vision-Language Models (VLM) have enabled efficient transfer to downstream tasks even when limited labelled training data is available, as well as for text to be directly compared to image content. These properties of V ...

Reaction additives are critical in dictating the outcomes of chemical processes making their effective screening vital for research. Conventional high-throughput experimentation tools can screen multiple reaction components rapidly. However, they are prohi ...

Quantitative analysis of microstructural features on the nanoscale, including precipitates, local chemical orderings (LCOs) or structural defects (e.g. stacking faults) plays a pivotal role in understanding the mechanical and physical responses of engineer ...

Adversarial Confidence Estimation Networks for Robust Stereo Matching

Chattez avec Graph Search

Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-Dimensional Tokens

Automatic identification of atmospheric bioaerosol using real-time imaging and fluorescence

Pose-Invariant Face Recognition via Feature-Space Pose Frontalization

Nonparametric network summaries

Spotiflow: accurate and efficient spot detection for fluorescence microscopy with deep stereographic flow regression

Cross-Net: Joint In-Line Holographic Image Reconstruction and Refocusing

FADE: Forecasting for anomaly detection on ECG

GraphOntology Dataset

Anomaly Anything: Promptable Unseen Visual Anomaly Generation

From Prediction to Prescription: Machine Learning and Causal Inference for the Heterogeneous Treatment Effect

Multi-Objective Management for Many-Core Computing Servers

GeoDistill: Geometry-Guided Self-Distillation for Weakly Supervised Cross-View Localization

Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks

Project-Based Learning Approach for an Engineering Course: Challenges and Learnings of Teaching Transversal Skills

Online Learning of Continuous Signed Distance Fields Using Piecewise Polynomials

Towards Robust Vision Models

Intraday solar irradiance forecasting using public cameras

Prompt-guided and multimodal landscape scenicness assessments with vision-language models

Bayesian optimisation for additive screening and yield improvements - beyond one-hot encoding

3D deep learning for enhanced atom probe tomography analysis of nanoscale microstructures