Search Results for author: Marco Bertini

Found 13 papers, 5 papers with code

Task-conditioned Domain Adaptation for Pedestrian Detection in Thermal Imagery

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.

Domain Adaptation Pedestrian Detection

Error assessment of microwave holography inversion for shallow buried objects

no code implementations27 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.

Zero-Shot Composed Image Retrieval with Textual Inversion

2 code implementations27 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.

Benchmarking Image Retrieval +1

Partially fake it till you make it: mixing real and fake thermal images for improved object detection

no code implementations25 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.

Data Augmentation object-detection +1

Robust pedestrian detection in thermal imagery using synthesized images

no code implementations3 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.

Data Augmentation Domain Adaptation +1

Inner Eye Canthus Localization for Human Body Temperature Screening

no code implementations27 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.

Face Model

Image Retrieval using Multi-scale CNN Features Pooling

no code implementations21 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.

Image Retrieval Retrieval

Deep Generative Adversarial Compression Artifact Removal

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.

object-detection Object Detection +1

Compact Hash Codes for Efficient Visual Descriptors Retrieval in Large Scale Databases

no code implementations10 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.


Socializing the Semantic Gap: A Comparative Survey on Image Tag Assignment, Refinement and Retrieval

1 code implementation28 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.

Content-Based Image Retrieval Retrieval +1

A Data-Driven Approach for Tag Refinement and Localization in Web Videos

no code implementations2 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.


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