279 citations · 1.1k across the 55 of their papers we have counts for
60 papers
One Patch to Caption Them All: A Unified Zero-Shot Captioning Framework
Lorenzo Bianchi, Giacomo Pacini, Fabio Carrara +3
Zero-shot captioners are recently proposed models that utilize common-space vision-language representations to caption images without relying on paired image-text data. To caption…
Learning Egocentric In-Hand Object Segmentation through Weak Supervision from Human Narrations
Nicola Messina, Rosario Leonardi, Luca Ciampi +4
Pixel-level recognition of objects manipulated by the user from egocentric images enables key applications spanning assistive technologies, industrial safety, and activity monitori…
CA3D: Convolutional-Attentional 3D Nets for Efficient Video Activity Recognition on the Edge
Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro +1
In this paper, we introduce a deep learning solution for video activity recognition that leverages an innovative combination of convolutional layers with a linear-complexity attent…
CountingDINO: A Training-free Pipeline for Class-Agnostic Counting using Unsupervised Backbones
Giacomo Pacini, Lorenzo Bianchi, Luca Ciampi +3
Class-agnostic counting (CAC) aims to estimate the number of objects in images without being restricted to predefined categories. However, while current exemplar-based CAC methods…
Semi-Supervised Biomedical Image Segmentation via Diffusion Models and Teacher-Student Co-Training
Luca Ciampi, Gabriele Lagani, Giuseppe Amato +1
Supervised deep learning achieves strong performance in biomedical image segmentation but relies on costly pixel-wise annotations, motivating semi-supervised approaches that exploi…
A Survey on Class-Agnostic Counting: Advancements from Reference-Based to Open-World Text-Guided Approaches
Luca Ciampi, Ali Azmoudeh, Elif Ecem Akbaba +5
Visual object counting has recently shifted towards class-agnostic counting (CAC), which addresses the challenge of counting objects across arbitrary categories, a crucial capabili…
Maybe you are looking for CroQS: Cross-modal Query Suggestion for Text-to-Image Retrieval
Giacomo Pacini, Fabio Carrara, Nicola Messina +3
Query suggestion, a technique widely adopted in information retrieval, enhances system interactivity and the browsing experience of document collections. In cross-modal retrieval,…
Biologically-inspired Semi-supervised Semantic Segmentation for Biomedical Imaging
Luca Ciampi, Gabriele Lagani, Giuseppe Amato +1
We propose a novel bio-inspired semi-supervised learning approach for training downsampling-upsampling semantic segmentation architectures. The first stage does not use backpropaga…
Talking to DINO: Bridging Self-Supervised Vision Backbones with Language for Open-Vocabulary Segmentation
Luca Barsellotti, Lorenzo Bianchi, Nicola Messina +5
Open-Vocabulary Segmentation (OVS) aims at segmenting images from free-form textual concepts without predefined training classes. While existing vision-language models such as CLIP…
Exploring Strengths and Weaknesses of Super-Resolution Attack in Deepfake Detection
Davide Alessandro Coccomini, Roberto Caldelli, Fabrizio Falchi +2
Image manipulation is rapidly evolving, allowing the creation of credible content that can be used to bend reality. Although the results of deepfake detectors are promising, deepfa…
Mind the Prompt: A Novel Benchmark for Prompt-based Class-Agnostic Counting
Luca Ciampi, Nicola Messina, Matteo Pierucci +3
Recently, object counting has shifted towards class-agnostic counting (CAC), which counts instances of arbitrary object classes never seen during model training. With advancements…
Adversarial Magnification to Deceive Deepfake Detection through Super Resolution
Davide Alessandro Coccomini, Roberto Caldelli, Giuseppe Amato +2
Deepfake technology is rapidly advancing, posing significant challenges to the detection of manipulated media content. Parallel to that, some adversarial attack techniques have bee…
Joint-Dataset Learning and Cross-Consistent Regularization for Text-to-Motion Retrieval
Nicola Messina, Jan Sedmidubsky, Fabrizio Falchi +1
Pose-estimation methods enable extracting human motion from common videos in the structured form of 3D skeleton sequences. Despite great application opportunities, effective conten…
Animal Behavior Analysis Methods Using Deep Learning: A Survey
Edoardo Fazzari, Donato Romano, Fabrizio Falchi +1
Animal behavior serves as a reliable indicator of the adaptation of organisms to their environment and their overall well-being. Through rigorous observation of animal actions and…
Is CLIP the main roadblock for fine-grained open-world perception?
Lorenzo Bianchi, Fabio Carrara, Nicola Messina +1
Modern applications increasingly demand flexible computer vision models that adapt to novel concepts not encountered during training. This necessity is pivotal in emerging domains…
Deepfake Detection without Deepfakes: Generalization via Synthetic Frequency Patterns Injection
Davide Alessandro Coccomini, Roberto Caldelli, Claudio Gennaro +3
Deepfake detectors are typically trained on large sets of pristine and generated images, resulting in limited generalization capacity; they excel at identifying deepfakes created t…
The devil is in the fine-grained details: Evaluating open-vocabulary object detectors for fine-grained understanding
Lorenzo Bianchi, Fabio Carrara, Nicola Messina +2
Recent advancements in large vision-language models enabled visual object detection in open-vocabulary scenarios, where object classes are defined in free-text formats during infer…
Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey
Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro +1
Recently emerged technologies based on Deep Learning (DL) achieved outstanding results on a variety of tasks in the field of Artificial Intelligence (AI). However, these encounter…
Spiking Neural Networks and Bio-Inspired Supervised Deep Learning: A Survey
Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro +1
For a long time, biology and neuroscience fields have been a great source of inspiration for computer scientists, towards the development of Artificial Intelligence (AI) technologi…
Text-to-Motion Retrieval: Towards Joint Understanding of Human Motion Data and Natural Language
Nicola Messina, Jan Sedmidubsky, Fabrizio Falchi +1
Due to recent advances in pose-estimation methods, human motion can be extracted from a common video in the form of 3D skeleton sequences. Despite wonderful application opportuniti…
The Emotions of the Crowd: Learning Image Sentiment from Tweets via Cross-modal Distillation
Alessio Serra, Fabio Carrara, Maurizio Tesconi +1
Trends and opinion mining in social media increasingly focus on novel interactions involving visual media, like images and short videos, in addition to text. In this work, we tackl…
Detecting Images Generated by Diffusers
Davide Alessandro Coccomini, Andrea Esuli, Fabrizio Falchi +2
This paper explores the task of detecting images generated by text-to-image diffusion models. To evaluate this, we consider images generated from captions in the MSCOCO and Wikimed…
MINTIME: Multi-Identity Size-Invariant Video Deepfake Detection
Davide Alessandro Coccomini, Giorgos Kordopatis Zilos, Giuseppe Amato +4
In this paper, we introduce MINTIME, a video deepfake detection approach that captures spatial and temporal anomalies and handles instances of multiple people in the same video and…
Deep learning for structural health monitoring: An application to heritage structures
Fabio Carrara, Fabrizio Falchi, Maria Girardi +3
Thanks to recent advancements in numerical methods, computer power, and monitoring technology, seismic ambient noise provides precious information about the structural behavior of…