Search Results for author: Tiberio Uricchio

Found 8 papers, 5 papers with code

Learning advisor networks for noisy image classification

1 code implementation ICIAP 2022 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.

Ranked #4 on Image Classification on Clothing1M (using extra training data)

Classification Learning with noisy labels +1

Learning Group Activities from Skeletons without Individual Action Labels

1 code implementation14 May 2021 Fabio Zappardino, Tiberio Uricchio, Lorenzo Seidenari, Alberto del Bimbo

To understand human behavior we must not just recognize individual actions but model possibly complex group activity and interactions.

Group Activity Recognition

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

Automatic Image Annotation via Label Transfer in the Semantic Space

no code implementations16 May 2016 Tiberio Uricchio, Lamberto Ballan, Lorenzo Seidenari, Alberto del Bimbo

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 that are able to search and browse large-scale image collections.

Denoising

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

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