3 citations · 9 across the 12 of their papers we have counts for
13 papers
Cross the Gap: Exposing the Intra-modal Misalignment in CLIP via Modality Inversion
Marco Mistretta, Alberto Baldrati, Lorenzo Agnolucci +2
Pre-trained multi-modal Vision-Language Models like CLIP are widely used off-the-shelf for a variety of applications. In this paper, we show that the common practice of individuall…
Image Intrinsic Scale Assessment: Bridging the Gap Between Quality and Resolution
Vlad Hosu, Lorenzo Agnolucci, Daisuke Iso +1
Image Quality Assessment (IQA) measures and predicts perceived image quality by human observers. Although recent studies have highlighted the critical influence that variations in…
AIM 2024 Challenge on UHD Blind Photo Quality Assessment
Vlad Hosu, Marcos V. Conde, Lorenzo Agnolucci +3
We introduce the AIM 2024 UHD-IQA Challenge, a competition to advance the No-Reference Image Quality Assessment (NR-IQA) task for modern, high-resolution photos. The challenge is b…
UHD-IQA Benchmark Database: Pushing the Boundaries of Blind Photo Quality Assessment
Vlad Hosu, Lorenzo Agnolucci, Oliver Wiedemann +2
We introduce a novel Image Quality Assessment (IQA) dataset comprising 6073 UHD-1 (4K) images, annotated at a fixed width of 3840 pixels. Contrary to existing No-Reference (NR) IQA…
iSEARLE: Improving Textual Inversion for Zero-Shot Composed Image Retrieval
Lorenzo Agnolucci, Alberto Baldrati, Alberto Del Bimbo +1
Given a query consisting of a reference image and a relative caption, Composed Image Retrieval (CIR) aims to retrieve target images visually similar to the reference one while inco…
Quality-Aware Image-Text Alignment for Opinion-Unaware Image Quality Assessment
Lorenzo Agnolucci, Leonardo Galteri, Marco Bertini
No-Reference Image Quality Assessment (NR-IQA) focuses on designing methods to measure image quality in alignment with human perception when a high-quality reference image is unava…
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…
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…
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…
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…
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.…
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…
Zero-Shot Composed Image Retrieval with Textual Inversion
Alberto Baldrati, Lorenzo Agnolucci, Marco Bertini +1
Composed Image Retrieval (CIR) aims to retrieve a target image based on a query composed of a reference image and a relative caption that describes the difference between the two i…