56 citations · 94 across the 20 of their papers we have counts for
22 papers
Resonant Brane Splatting for Arbitrary-Scale Super-Resolution
Giulio Federico, Giuseppe Amato, Claudio Gennaro +2
Arbitrary-Scale Super-Resolution (ASR) reconstructs images at continuous magnification factors. Recent methods accelerate inference by replacing computationally heavy implicit neur…
Adaptive Densification for High-Fidelity and Efficient Sparse Gaussian Splatting in Arbitrary-Scale Super-Resolution
Giulio Federico, Giuseppe Amato, Claudio Gennaro +2
Arbitrary-Scale Super-Resolution (ASR) aims to reconstruct high-resolution images at any continuous magnification. While 2D Gaussian Splatting (GS) has recently shown great promise…
Reviving ConvNeXt for Efficient Convolutional Diffusion Models
Taesung Kwon, Lorenzo Bianchi, Lennart Wittke +5
Recent diffusion models increasingly favor Transformer backbones, motivated by the remarkable scalability of fully attentional architectures. Yet the locality bias, parameter effic…
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…
LoomNet: Enhancing Multi-View Image Generation via Latent Space Weaving
Giulio Federico, Fabio Carrara, Claudio Gennaro +2
Generating consistent multi-view images from a single image remains challenging. Lack of spatial consistency often degrades 3D mesh quality in surface reconstruction. To address th…
ViSketch-GPT: Collaborative Multi-Scale Feature Extraction for Sketch Recognition and Generation
Giulio Federico, Giuseppe Amato, Fabio Carrara +2
Understanding the nature of human sketches is challenging because of the wide variation in how they are created. Recognizing complex structural patterns improves both the accuracy…
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,…
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…
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…
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…
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…
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…
Recurrent Vision Transformer for Solving Visual Reasoning Problems
Nicola Messina, Giuseppe Amato, Fabio Carrara +2
Although convolutional neural networks (CNNs) showed remarkable results in many vision tasks, they are still strained by simple yet challenging visual reasoning problems. Inspired…
Multi-Camera Vehicle Counting Using Edge-AI
Luca Ciampi, Claudio Gennaro, Fabio Carrara +3
This paper presents a novel solution to automatically count vehicles in a parking lot using images captured by smart cameras. Unlike most of the literature on this task, which focu…
Solving the Same-Different Task with Convolutional Neural Networks
Nicola Messina, Giuseppe Amato, Fabio Carrara +2
Deep learning demonstrated major abilities in solving many kinds of different real-world problems in computer vision literature. However, they are still strained by simple reasonin…
Combining GANs and AutoEncoders for Efficient Anomaly Detection
Fabio Carrara, Giuseppe Amato, Luca Brombin +2
In this work, we propose CBiGAN -- a novel method for anomaly detection in images, where a consistency constraint is introduced as a regularization term in both the encoder and dec…
The VISIONE Video Search System: Exploiting Off-the-Shelf Text Search Engines for Large-Scale Video Retrieval
Giuseppe Amato, Paolo Bolettieri, Fabio Carrara +5
In this paper, we describe in details VISIONE, a video search system that allows users to search for videos using textual keywords, occurrence of objects and their spatial relation…
Automatic Pass Annotation from Soccer VideoStreams Based on Object Detection and LSTM
Danilo Sorano, Fabio Carrara, Paolo Cintia +2
Soccer analytics is attracting increasing interest in academia and industry, thanks to the availability of data that describe all the spatio-temporal events that occur in each matc…
Detection of Face Recognition Adversarial Attacks
Fabio Valerio Massoli, Fabio Carrara, Giuseppe Amato +1
Deep Learning methods have become state-of-the-art for solving tasks such as Face Recognition (FR). Unfortunately, despite their success, it has been pointed out that these learnin…
Exploring epoch-dependent stochastic residual networks
Fabio Carrara, Andrea Esuli, Fabrizio Falchi +1
The recently proposed stochastic residual networks selectively activate or bypass the layers during training, based on independent stochastic choices, each of which following a pro…
Picture It In Your Mind: Generating High Level Visual Representations From Textual Descriptions
Fabio Carrara, Andrea Esuli, Tiziano Fagni +2
In this paper we tackle the problem of image search when the query is a short textual description of the image the user is looking for. We choose to implement the actual search pro…