Risultati di ricerca
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N. Messina, G. Amato, F. Carrara, F. Falchi, C. Gennaro: "Learning Relationship-aware Visual Features". In Computer Vision – ECCV 2018 Workshops. (Vol. 4, pp. 486–501). Springer, Cham
Abstract: Relational reasoning in Computer Vision has recently shown impressive results on visual question answering tasks. On the challenging dataset called CLEVR, the recently proposed Relation Network (RN), a simple plug-and-play module and one of...
https://phd.dii.unipi.it/publications/item/2537-messina,-n-,-amato,-g-,-carrara,-f-,-falchi,-f-,-and-gennaro,-c-2018,-september-learning-relationship-aware-visual-features-in-computer-vision-–-eccv-2018-workshops-vol-4,-pp-486–501-springer,-cham.html -
F. Carrara, R. Becarelli, R. Caldelli, F. Falchi, G. Amato: "Adversarial examples detection in features distance spaces". In Computer Vision – ECCV 2018 Workshops. (Vol. 2, pp. 313–327). Springer, Cham.
Abstract: Maliciously manipulated inputs for attacking machine learning methods–in particular deep neural networks–are emerging as a relevant issue for the security of recent artificial intelligence technologies, especially in computer vision. In this...
https://phd.dii.unipi.it/publications/item/2538-f-carrara,-r-becarelli,-r-caldelli,-f-falchi,-g-amato-adversarial-examples-detection-in-features-distance-spaces-in-computer-vision-–-eccv-2018-workshops-vol-2,-pp-313–327-springer,-cham.html -
G. Amato, P. Bolettieri, F. Carrara, F. Falchi, C. Gennaro: "Large-Scale Image Retrieval with Elasticsearch", In Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, pp. 925-928
Content-Based Image Retrieval in large archives through the use of visual features has become a very attractive research topic in recent years. The cause of this strong impulse in this area of research is certainly to be attributed to the use of...
https://phd.dii.unipi.it/pubblicazioni/item/2199-g-amato,-p-bolettieri,-f-carrara,-f-falchi,-c-gennaro-large-scale-image-retrieval-with-elasticsearch-,-in-proceedings-of-the-41st-international-acm-sigir-conference-on-research-development-in-information-retrieval,-pp-925-928.html -
F. Carrara, F. Falchi, R. Caldelli, G. Amato, R. Becarelli: "Adversarial image detection in deep neural networks", Multimedia Tools and Applications, 1-21
Deep neural networks are more and more pervading many computer vision applications and in particular image classification. Notwithstanding that, recent works have demonstrated that it is quite easy to create adversarial examples, i.e., images...
https://phd.dii.unipi.it/pubblicazioni/item/2198-f-carrara,-f-falchi,-r-caldelli,-g-amato,-r-becarelli-adversarial-image-detection-in-deep-neural-networks-,-multimedia-tools-and-applications,-1-21.html -
L. Vadicamo, F. Carrara, A. Cimino, S. Cresci, F. Dell’Orletta, F. Falchi, M. Tesconi: “Cross-Media Learning for Image Sentiment Analysis in the Wild”, Proceedings of the 5th Workshop on Web-scale Vision and Social Media (VSM), ICCV 2017
Much progress has been made in the field of sentiment analysis in the past years. Researchers relied on textual data for this task, while only recently they have started in- vestigating approaches to predict sentiments from multime- dia content. With...
https://phd.dii.unipi.it/pubblicazioni/item/1653-l-vadicamo,-f-carrara,-a-cimino,-s-cresci,-f-dell’orletta,-f-falchi,-m-tesconi-“cross-media-learning-for-image-sentiment-analysis-in-the-wild”,-proceedings-of-the-5th-workshop-on-web-scale-vision-and-social-media-vsm-,-iccv-2017.html -
G. Amato, F. Carrara, F. Falchi, C. Gennaro, C. Meghini, C.Vairo: "Deep Learning for Decentralized Parking Lot Occupancy Detection", ESWA Expert Systems with Applications Journal 72, 327-334
A smart camera is a vision system capable of extracting application-specific information from the captured images. The paper proposes a decentralized and efficient solution for visual parking lot occupancy detection based on a deep Convolutional Neural...
https://phd.dii.unipi.it/pubblicazioni/item/1652-g-amato,-f-carrara,-f-falchi,-c-gennaro,-c-meghini,-c-vairo-deep-learning-for-decentralized-parking-lot-occupancy-detection-,-eswa-expert-systems-with-applications-journal-72,-327-334.html -
F. Carrara, F. Falchi, R. Caldelli, G. Amato, R. Fumarola, R. Becarelli, “Detecting adversarial example attacks to deep neural networks”, Proceedings of the 15th International Workshop on Content-Based Multimedia Indexing (CBMI), June 2017
Deep learning has recently become the state of the art in many computer vision applications and in image classification in particular. However, recent works have shown that it is quite easy to create adversarial examples, i.e., images intentionally...
https://phd.dii.unipi.it/pubblicazioni/item/1651-f-carrara,-f-falchi,-r-caldelli,-g-amato,-r-fumarola,-r-becarelli,-“detecting-adversarial-example-attacks-to-deep-neural-networks”,-proceedings-of-the-15th-international-workshop-on-content-based-multimedia-indexing-cbmi-,-june-2017.html -
G. Amato, F. Carrara, F. Falchi, C. Gennaro: “Efficient Indexing of Regional Maximum Activations of Convolutions using Full-Text Search Engines”, Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval (ICMR), June 2017
In this paper, we adapt a surrogate text representation technique to develop efficient instance-level image retrieval using Regional Maximum Activations of Convolutions (R-MAC). R-MAC features have recently showed outstanding performance in visual...
https://phd.dii.unipi.it/pubblicazioni/item/1650-g-amato,-f-carrara,-f-falchi,-c-gennaro-“efficient-indexing-of-regional-maximum-activations-of-convolutions-using-full-text-search-engines”,-proceedings-of-the-2017-acm-on-international-conference-on-multimedia-retrieval-icmr-,-june-2017.html -
F. Carrara, A. Esuli, T. Fagni, F. Falchi, A.M. Fernández: "Picture It In Your Mind: Generating High Level Visual Representations From Textual Descriptions", Neu-IR '16 SIGIR non-archival Workshop on Neural Information Retrieval
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 process as a similarity search in a visual feature space, by learning to...
https://phd.dii.unipi.it/pubblicazioni/item/1649-f-carrara,-a-esuli,-t-fagni,-f-falchi,-am-fernández-picture-it-in-your-mind-generating-high-level-visual-representations-from-textual-descriptions-,-neu-ir-sigir-2016-workshop-on-neural-information-retrieval,-july-21,-2016,-pisa,-italy.html -
G. Amato, F. Carrara, F. Falchi, C. Gennaro, C. Vairo: "Car parking occupancy detection using smart camera networks and Deep Learning", 2016 IEEE Symposium on Computers and Communication (ISCC), 1212-1217
This paper presents an approach for real-time car parking occupancy detection that uses a Convolutional Neural Network (CNN) classifier running on-board of a smart camera with limited resources. Experiments show that our technique is very effective and...
https://phd.dii.unipi.it/pubblicazioni/item/1074-g-amato,-f-carrara,-f-falchi,-c-gennaro,-c-vairo-car-parking-occupancy-detection-using-smart-camera-networks-and-deep-learning-,-2016-ieee-symposium-on-computers-and-communication-iscc-,-1212-1217.html -
Carrara F, Falchi F, Gennaro C. Semiautomatic Learning of 3D Objects from Video Streams. Similarity Search and Applications. 2015:217-28.
Object detection and recognition are classical problems in computer vision, but are still challenging without a priori knowledge of objects and with a limited user interaction. In this work, a semiautomatic system for visual object learning from video...
https://phd.dii.unipi.it/pubblicazioni/item/805-carrara-f,-falchi-f,-gennaro-c-semiautomatic-learning-of-3d-objects-from-video-streams-similarity-search-and-applications-2015-217-28.html -
Carrara F, Amato G, Falchi F, Gennaro C. Efficient foreground-background segmentation using local features for object detection. InProceedings of the 9th International Conference on Distributed Smart Camera 2015 Sep 8 (pp. 175-180). ACM.
In this work, a local feature based background modelling for background-foreground feature segmentation is presented. In local feature based computer vision applications, a local feature based model presents advantages with respect to classical...
https://phd.dii.unipi.it/pubblicazioni/item/804-carrara-f,-amato-g,-falchi-f,-gennaro-c-efficient-foreground-background-segmentation-using-local-features-for-object-detection-inproceedings-of-the-9th-international-conference-on-distributed-smart-camera-2015-sep-8-pp-175-180-acm.html
