most citedARNIQA: Learning Distortion Manifold for Image Quality Assessment

3 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2023

Perceptual Quality Improvement in Videoconferencing using Keyframes-based GAN

Lorenzo Agnolucci, Leonardo Galteri, Marco Bertini +1

In the latest years, videoconferencing has taken a fundamental role in interpersonal relations, both for personal and business purposes. Lossy video compression algorithms are the…

cs.CV2023

Restoration of Analog Videos Using Swin-UNet

Lorenzo Agnolucci, Leonardo Galteri, Marco Bertini +1

In this paper, we present a system to restore analog videos of historical archives. These videos often contain severe visual degradation due to the deterioration of their tape supp…

cs.CV20233 cited

ARNIQA: Learning Distortion Manifold for Image Quality Assessment

Lorenzo Agnolucci, Leonardo Galteri, Marco Bertini +1

No-Reference Image Quality Assessment (NR-IQA) aims to develop methods to measure image quality in alignment with human perception without the need for a high-quality reference ima…

cs.CV2023

Reference-based Restoration of Digitized Analog Videotapes

Lorenzo Agnolucci, Leonardo Galteri, Marco Bertini +1

Analog magnetic tapes have been the main video data storage device for several decades. Videos stored on analog videotapes exhibit unique degradation patterns caused by tape aging…

cs.CV2023

Mapping Memes to Words for Multimodal Hateful Meme Classification

Giovanni Burbi, Alberto Baldrati, Lorenzo Agnolucci +2

Multimodal image-text memes are prevalent on the internet, serving as a unique form of communication that combines visual and textual elements to convey humor, ideas, or emotions.…

cs.CV2023

ECO: Ensembling Context Optimization for Vision-Language Models

Lorenzo Agnolucci, Alberto Baldrati, Francesco Todino +3

Image recognition has recently witnessed a paradigm shift, where vision-language models are now used to perform few-shot classification based on textual prompts. Among these, the C…