4 citations · 8 across the 14 of their papers we have counts for
15 papers
KARAMEL: Knowledge-Aware Ranking for Multimodal Entity Linking in the Arts via Heterogeneous Graphs
Raffaele Scaringi, Alejandro Sierra-Múnera, Gennaro Vessio +2
Discovering and disambiguating entities from multimodal and heterogeneous data is a key challenge in discovery science, where relevant knowledge is often implicit and distributed a…
A Diffusion-Based Kinematics and Dynamics Model for 3D Sign Language Production
Emanuele Colonna, Moises Diaz, Gennaro Vessio +2
Sign Language Production (SLP) generates continuous signing from a linguistic input and drives accessibility technologies such as signing avatars. Current generators, diffusion mod…
Understanding How MLLMs Describe Artworks Using Token Activation Maps
Nicola Fanelli, Pasquale De Marinis, Raffaele Scaringi +3
Multimodal Large Language Models (MLLMs) describe artworks with remarkable fluency, yet the visual reasoning behind their outputs remains opaque. When an MLLM names a style, identi…
Analyzing the Correlation Between Hallucinations and Knowledge Conflicts in Large Language Models
Lucrezia Laraspata, Giovanna Castellano, Gennaro Vessio
Hallucinations -- factually incorrect or unverifiable outputs -- remain one of the most challenging limitations of Large Language Models (LLMs), especially in knowledge-intensive t…
Art2Mus: Artwork-to-Music Generation via Visual Conditioning and Large-Scale Cross-Modal Alignment
Ivan Rinaldi, Matteo Mendula, Nicola Fanelli +4
Music generation has advanced markedly through multimodal deep learning, enabling models to synthesize audio from text and, more recently, from images. However, existing image-cond…
DistillFSS: Synthesizing Few-Shot Knowledge into a Lightweight Segmentation Model
Pasquale De Marinis, Pieter M. Blok, Uzay Kaymak +3
Cross-Domain Few-Shot Semantic Segmentation (CD-FSS) seeks to segment unknown classes in unseen domains using only a few annotated examples. This setting is inherently challenging:…
Take a Peek: Efficient Encoder Adaptation for Few-Shot Semantic Segmentation via LoRA
Pasquale De Marinis, Gennaro Vessio, Giovanna Castellano
Few-shot semantic segmentation (FSS) aims to segment novel classes in query images using only a small annotated support set. While prior research has mainly focused on improving de…
Matching-Based Few-Shot Semantic Segmentation Models Are Interpretable by Design
Pasquale De Marinis, Uzay Kaymak, Rogier Brussee +2
Few-Shot Semantic Segmentation (FSS) models achieve strong performance in segmenting novel classes with minimal labeled examples, yet their decision-making processes remain largely…
Modeling and benchmarking quantum optical neurons for efficient neural computation
Andrea Andrisani, Gennaro Vessio, Fabrizio Sgobba +3
Quantum optical neurons (QONs) are emerging as promising computational units that leverage photonic interference to perform neural operations in an energy-efficient and physically…
ArtSeek: Deep artwork understanding via multimodal in-context reasoning and late interaction retrieval
Nicola Fanelli, Gennaro Vessio, Giovanna Castellano
Analyzing digitized artworks requires both visual interpretation and deep artistic, contextual, and historical knowledge. We introduce ArtSeek, a multimodal framework for art analy…
I Dream My Painting: Connecting MLLMs and Diffusion Models via Prompt Generation for Text-Guided Multi-Mask Inpainting
Nicola Fanelli, Gennaro Vessio, Giovanna Castellano
Inpainting focuses on filling missing or corrupted regions of an image to blend seamlessly with its surrounding content and style. While conditional diffusion models have proven ef…
Neural network modelling of kinematic and dynamic features for signature verification
Moises Diaz, Miguel A. Ferrer, Jose Juan Quintana +5
Online signature parameters, which are based on human characteristics, broaden the applicability of an automatic signature verifier. Although kinematic and dynamic features have pr…
RoWeeder: Unsupervised Weed Mapping through Crop-Row Detection
Pasquale De Marinis, Gennaro Vessio, Giovanna Castellano
Precision agriculture relies heavily on effective weed management to ensure robust crop yields. This study presents RoWeeder, an innovative framework for unsupervised weed mapping…
Art2Mus: Bridging Visual Arts and Music through Cross-Modal Generation
Ivan Rinaldi, Nicola Fanelli, Giovanna Castellano +1
Artificial Intelligence and generative models have revolutionized music creation, with many models leveraging textual or visual prompts for guidance. However, existing image-to-mus…
Label Anything: Multi-Class Few-Shot Semantic Segmentation with Visual Prompts
Pasquale De Marinis, Nicola Fanelli, Raffaele Scaringi +4
Few-shot semantic segmentation aims to segment objects from previously unseen classes using only a limited number of labeled examples. In this paper, we introduce Label Anything, a…