122 citations · 225 across the 10 of their papers we have counts for
9 papers · 1 filter
A Semi-Automated Framework for 3D Reconstruction of Medieval Manuscript Miniatures
Riccardo Pallotto, Pierluigi Feliciati, Tiberio Uricchio
This paper presents a semi-automated framework for transforming two-dimensional miniatures from medieval manuscripts into three-dimensional digital models suitable for extended rea…
Prompt-based Consistent Video Colorization
Silvia Dani, Tiberio Uricchio, Lorenzo Seidenari
Existing video colorization methods struggle with temporal flickering or demand extensive manual input. We propose a novel approach automating high-fidelity video colorization usin…
Exploiting CLIP-based Multi-modal Approach for Artwork Classification and Retrieval
Alberto Baldrati, Marco Bertini, Tiberio Uricchio +1
Given the recent advances in multimodal image pretraining where visual models trained with semantically dense textual supervision tend to have better generalization capabilities th…
Composed Image Retrieval using Contrastive Learning and Task-oriented CLIP-based Features
Alberto Baldrati, Marco Bertini, Tiberio Uricchio +1
Given a query composed of a reference image and a relative caption, the Composed Image Retrieval goal is to retrieve images visually similar to the reference one that integrates th…
Learning advisor networks for noisy image classification
Simone Ricci, Tiberio Uricchio, Alberto Del Bimbo
In this paper, we introduced the novel concept of advisor network to address the problem of noisy labels in image classification. Deep neural networks (DNN) are prone to performanc…
Learning Group Activities from Skeletons without Individual Action Labels
Fabio Zappardino, Tiberio Uricchio, Lorenzo Seidenari +1
To understand human behavior we must not just recognize individual actions but model possibly complex group activity and interactions. Hierarchical models obtain the best results i…
Image Retrieval using Multi-scale CNN Features Pooling
Federico Vaccaro, Marco Bertini, Tiberio Uricchio +1
In this paper, we address the problem of image retrieval by learning images representation based on the activations of a Convolutional Neural Network. We present an end-to-end trai…
Am I Done? Predicting Action Progress in Videos
Federico Becattini, Tiberio Uricchio, Lorenzo Seidenari +2
In this paper we deal with the problem of predicting action progress in videos. We argue that this is an extremely important task since it can be valuable for a wide range of inter…
Automatic Image Annotation via Label Transfer in the Semantic Space
Tiberio Uricchio, Lamberto Ballan, Lorenzo Seidenari +1
Automatic image annotation is among the fundamental problems in computer vision and pattern recognition, and it is becoming increasingly important in order to develop algorithms th…