Publications by Evgeniy Upenik

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Omnidirectional imaging has reached a level of widespread availability driven by recent advances in integrated circuit technology, image sensors, and computer graphics which allow now capturing, rendering and displaying of such type of immersive content in ...

Lossy image compression is a popular, simple and effective solution to reduce the amount of data representing digital pictures. In most lossy compression methods, the reduced volume of data in bits is achieved at the expense of introducing visual artifacts ...

Due to the increasing number of pictures captured and stored every day by and on digital devices, lossy image compression has become inevitable to limit the needed storage requirement. As a consequence, these compression methods might introduce some visual ...

JPEG image coding standard has been a dominant format in a wide range of applications in soon three decades since it has been released as an international standard. The landscape of applications and services based on pictures has evolved since the original ...

The image compression field is witnessing a shift in paradigm thanks to the rise of neural network-based models. In this context, the JPEG committee is in the process of standardizing the first learning-based image compression standard, known as JPEG AI. W ...

JPEG XL is a practical, royalty-free codec for scalable web distribution and efficient compression of high-quality photographs. It also includes previews, progressiveness, animation, transparency, high dynamic range, wide color gamut, and high bit depth. U ...

Learning-based image codecs produce different compression artifacts, when compared to the blocking and blurring degradation introduced by conventional image codecs, such as JPEG, JPEG~2000 and HEIC. In this paper, a crowdsourcing based subjective quality e ...

Omnidirectional image and video have gained popularity thanks to availability of capture and display devices for this type of content. Recent studies have assessed performance of objective metrics in predicting visual quality of omnidirectional content. Th ...

In person re-identification, individuals must be correctly identified in images that come from different cameras or are captured at different points in time. In the open-set case, the above needs be achieved for people who have not been previously recognis ...

Recently, there has been an increased interest in capture, processing and rendering of visual content in form of point clouds. Among other challenges, subjective and objective quality evaluation of point clouds are still open problems. Most proposed subjec ...

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 ...

Automatic prediction of salient regions in images is a well developed topic in the field of computer vision. Yet, virtual reality omnidirectional visual content brings new challenges to this topic, due to a different representation of visual information an ...

The problem of objectively measuring perceptual quality of omnidirectional visual content arises in many immersive imaging applications and particularly in compression. The interactive nature of this type of content limits the performance of earlier method ...

Omnidirectional visual content is a form of representing graphical and cinematic media content which provides subjects with the ability to freely change the direction of view. Along with virtual reality, omnidirectional imaging is becoming a very important ...

There is a need for affordable and easily deployable rendering and display solutions to take full advantage of light field imaging. In particular, the research community needs ways to better assess the impact of various light field imaging technologies bas ...

Evgeniy Upenik

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Visual Attention and Perceptual Quality in Omnidirectional Imaging

Performance Evaluation of Objective Image Quality Metrics on Conventional and Learning-Based Compression Artifacts

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

Comprehensive assessment of image compression algorithms

On the impact of learning-based image compression on computer vision tasks

Benchmarking JPEG XL image compression

Large-Scale Crowdsourcing Subjective Quality Evaluation of Learning-Based Image Coding

On the performance of objective metrics for omnidirectional visual content

Open-Set Person Re-Identification through Error Resilient Recurring Gallery Building

Towards subjective quality assessment of point cloud imaging in augmented reality

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

A simple method to obtain visual attention data in head mounted virtual reality

Saliency Driven Perceptual Quality Metric for Omnidirectional Visual Content

Testbed for subjective evaluation of omnidirectional visual content

A Rendering Solution to Display Light Field in Virtual Reality