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Marco Bertini

Università degli Studi di Firenze

24 papers hereh-index 395.8k citations224 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author23
  • last author1

Across the 24 of 24 papers where every author was matched, so the position is known.

fields
  • cs.CV21
  • cs.CL1
  • cs.MM1
  • eess.IV1
affiliations
  • Università degli Studi di Firenze
HomepageORCID 0000-0002-1364-218X
same name
  • Marco Bertini — 6 papers, h 7
  • Marco Bertini — 2 papers, h 18

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162024
most citedExploiting CLIP-based Multi-modal Approach for Artwork Classification and Retrieval

7 citations · 14 across the 16 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.CV2024

Garment Attribute Manipulation with Multi-level Attention

Vittorio Casula, Lorenzo Berlincioni, Luca Cultrera +5

In the rapidly evolving field of online fashion shopping, the need for more personalized and interactive image retrieval systems has become paramount. Existing methods often strugg…

cs.CL2024

Prompt and Prejudice

Lorenzo Berlincioni, Luca Cultrera, Federico Becattini +2

This paper investigates the impact of using first names in Large Language Models (LLMs) and Vision Language Models (VLMs), particularly when prompted with ethical decision-making t…

cs.CV2024★ 2 cited

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…

cs.CV2024★ 1 cited

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…

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