1 code implementation • ECCV 2020 • My Kieu, Andrew D. Bagdanov, Marco Bertini, Alberto del Bimbo
Despite its broad application and interest, it remains a challenging problem in part due to the vast range of conditions under which it must be robust.
no code implementations • 27 Mar 2023 • Emanuele Vivoli, Luca Bossi, Marco Bertini, Pierluigi Falorni, Lorenzo Capineri
Holographic imaging is a technique that uses microwave energy to create a three-dimensional image of an object or scene.
2 code implementations • 27 Mar 2023 • Alberto Baldrati, Lorenzo Agnolucci, Marco Bertini, Alberto del Bimbo
Composed Image Retrieval (CIR) aims to retrieve a target image based on a query composed of a reference image and a relative caption that describes the difference between the two images.
2 code implementations • CVPRW 2022 • Alberto Baldrati, Marco Bertini, Tiberio Uricchio, Alberto del Bimbo
The proposed method is based on an initial training stage where a simple combination of visual and textual features is used, to fine-tune the CLIP text encoder.
Ranked #2 on Image Retrieval on Fashion IQ
2 code implementations • CVPR 2022 • Alberto Baldrati, Marco Bertini, Tiberio Uricchio, Alberto del Bimbo
the visual content of the query image.
Ranked #4 on Image Retrieval on CIRR
no code implementations • 25 Jun 2021 • Francesco Bongini, Lorenzo Berlincioni, Marco Bertini, Alberto del Bimbo
In this paper we propose a novel data augmentation approach for visual content domains that have scarce training datasets, compositing synthetic 3D objects within real scenes.
no code implementations • 3 Feb 2021 • My Kieu, Lorenzo Berlincioni, Leonardo Galteri, Marco Bertini, Andrew D. Bagdanov, Alberto del Bimbo
Experimental results demonstrate the effectiveness of our approach: using less than 50\% of available real thermal training data, and relying on synthesized data generated by our model in the domain adaptation phase, our detector achieves state-of-the-art results on the KAIST Multispectral Pedestrian Detection Benchmark; even if more real thermal data is available adding GAN generated images to the training data results in improved performance, thus showing that these images act as an effective form of data augmentation.
no code implementations • 27 Aug 2020 • Claudio Ferrari, Lorenzo Berlincioni, Marco Bertini, Alberto del Bimbo
As additional contribution, we enrich the original dataset by using the annotated landmarks to deform and project the 3DMM onto the images.
no code implementations • 21 Apr 2020 • Federico Vaccaro, Marco Bertini, Tiberio Uricchio, Alberto del Bimbo
In this paper, we address the problem of image retrieval by learning images representation based on the activations of a Convolutional Neural Network.
no code implementations • ICCV 2017 • Leonardo Galteri, Lorenzo Seidenari, Marco Bertini, Alberto del Bimbo
Moreover we show that our approach can be used as a pre-processing step for object detection in case images are degraded by compression to a point that state-of-the art detectors fail.
no code implementations • 10 May 2016 • Simone Ercoli, Marco Bertini, Alberto del Bimbo
In this paper we present an efficient method for visual descriptors retrieval based on compact hash codes computed using a multiple k-means assignment.
1 code implementation • 28 Mar 2015 • Xirong Li, Tiberio Uricchio, Lamberto Ballan, Marco Bertini, Cees G. M. Snoek, Alberto del Bimbo
Where previous reviews on content-based image retrieval emphasize on what can be seen in an image to bridge the semantic gap, this survey considers what people tag about an image.
no code implementations • 2 Jul 2014 • Lamberto Ballan, Marco Bertini, Giuseppe Serra, Alberto del Bimbo
Our approach exploits collective knowledge embedded in user-generated tags and web sources, and visual similarity of keyframes and images uploaded to social sites like YouTube and Flickr, as well as web sources like Google and Bing.