Recovering Badly Exposed Objects From Digital Photos Using Internet Images

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Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

The invention relates to an Imaging sensor device in a stacked arrangement comprising: - a pixel array tier comprising a plurality of pixel segments each having a plurality of pixels for photon detection each providing a digital pixel output; - a processin ...

In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

Recent advances in image compression have made it both possible and desirable for image quality to approach the visually lossless range. However, the most commonly used subjective visual quality assessment protocols, e.g. those reported in ITU-T Rec. BT.50 ...

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 ...

To obtain a more complete understanding of material microstructure at the nanoscale and to gain profound insights into their properties, there is a growing need for more efficient and precise methods that can streamline the process of 3D imaging using a tr ...

Ultrafast ultrasound imaging, characterized by high frame rates, generates low-quality images. Convolutional neural networks (CNNs) have demonstrated great potential to enhance image quality without compromising the frame rate. However, CNNs have been most ...

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 ...

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 ...

Single-photon avalanche diodes (SPADs) are novel image sensors that record the arrival of individual photons at extremely high temporal resolution. In the past, they were only available as single pixels or small-format arrays, for various active imaging ap ...

The past decades have witnessed rapid growth in imaging as a major form of communication between individuals. Due to recent advances in capture, storage, delivery and display technologies, consumers demand improved perceptual quality while requiring reduce ...

Reinterpretable cameras are defined by their post-processing capabilities that exceed traditional imaging. We present "SoDaCam" that provides reinterpretable cameras at the granularity of photons, from photon-cubes acquired by single-photon devices. Photon ...

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 ...

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 ...

In recent years, new emerging immersive imaging modalities, e.g. light fields, have been receiving growing attention, becoming increasingly widespread over the years. Light fields are often captured through multi-camera arrays or plenoptic cameras, with th ...

Rationale and objectives: To prospectively evaluate feasibility and robustness of an accelerated T2 mapping sequence (GRAPPATINI) in brain imaging and to assess its synthetic T2-weighted images (sT2w) in comparison with a standard T2-weighted sequence (T2 ...

Systematic compositionality, or the ability to adapt to novel situations by creating a mental model of the world using reusable pieces of knowledge, remains a significant challenge in machine learning. While there has been considerable progress in the lang ...

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 ...

Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional n ...

This study presents a novel framework for evaluating the luminance measurement capabilities of High Dynamic Range (HDR) sensor cameras in indoor glare conditions. Results indicate that the practical usage range of the CSEM VIP camera is significantly lower ...

Recovering Badly Exposed Objects From Digital Photos Using Internet Images

Chattez avec Graph Search

Aggregating Spatial and Photometric Context for Photometric Stereo

Imaging sensor device using an array of single-photon avalanche diode photodetectors

Incorporating Projective Geometry into Deep Learning

On the assessment of high-quality images: advances on the JPEG AIC-3 activity

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

3D reconstruction of curvilinear one-dimensional objects viewed in transmission electron microscopy

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning

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

Seeing Photons in Color

Burst Vision Using Single-Photon Cameras

On the Performance of Subjective Visual Quality Assessment Protocols for Nearly Visually Lossless Image Compression

SoDaCam: Software-defined Cameras via Single-Photon Imaging

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

Neural Distributed Image Compression with Cross-Attention Feature Alignment

Towards learning-based denoising of light fields

Clinical feasibility and validation of the accelerated T2 mapping sequence GRAPPATINI in brain imaging

Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models

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

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation

Performance investigation of cameras using HDR sensors for daylight glare evaluations