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 ...

The methods of Content-Based visual information indexing and retrieval penetrate into Healthcare and become popular in Computer-Aided Diagnosis. Multimedia in medical images means different imaging modalities, but also multiple views of the same ...

This paper describes a system for semi-automatic quality assessment of user generated content (UGC) from large events. It uses image and video processing techniques1 combined with a computational quality model that takes in account aesthetics and how ...

This paper investigates two-types of shape representations for individual Maya codical glyphs: traditional bag-of-words built on knowledge-driven local shape descriptors (HOOSC), and Convolutional Neural Networks (CNN) based representations, learned ...

We consider the problem of image classification using deep convolutional networks, with respect to hierarchical relationships among classes. We investigate if the semantic hierarchy is captured by CNN models or not. For this we analyze the confidence of ...

Many new symmetry detection algorithms have been recently developed, thanks to an interest revival on computational symmetry for computer graphics and computer vision applications. Notably, in 2013 the IEEE CVPR Conference organized a dedicated workshop ...

This paper deals with automatic cartoon colorization. This is a hard issue, since it is an ill-posed problem that usually requires user intervention to achieve high quality. Motivated by the recent successes in natural image colorization based on deep ...

Scene labeling has been an important and popular area of computer vision and image processing for the past few years. It is the process of assigning pixels to specific predefined categories in an image. A number of techniques have been proposed for ...

Nowadays, deep learning is more and more used for Music Genre Classification: particularly Convolutional Neural Networks (CNN) taking as entry a spectrogram considered as an image on which are sought different types of structure.

But, facing the ...

The automatic description of multimedia content was mainly developed for classification tasks, retrieval systems and massive ordering of data. Preservation of cultural heritage is a field of high importance for application to this method. Our problem is ...

The indexing of broadcast TV archives is a current problem in multimedia research. As the size of these databases grows continuously, meaningful features are needed to describe and connect their elements efficiently, such as the identification of ...

This work investigated two different machine learning techniques: Cascade Learning and Deep Learning, to find out which algorithm performs better to detect the number plate of vehicles registered in Bangladesh. To do this, we created a dataset of about ...

Detecting text in natural scene images is a challenging task. In this paper, we propose a character-level end-to-end text detection algorithm in natural scene images. In general, text detection tasks are categorized into three parts: text localization, ...

Online activities such as social networking, shopping, and consuming multi-media create digital traces often used to improve user experience and increase revenue, e.g., through better-fitting recommendations and targeted marketing. We investigate to ...

We present a supervised dimensionality reduction technique suitable for visualizing multi-label images on a 2-D space. This method extends the use of the well-known t-distributed stochastic embedding (t-SNE) algorithm to the case of multi-labels ...

The development of powerful 3D scanning hardware and reconstruction algorithms has strongly promoted the generation of 3D surface reconstructions in different domains. An area of special interest for such 3D reconstructions is the cultural heritage ...

Visual Question Answering (VQA), a task that requires the ability to provide an answer to a question given an image, has recently become an important benchmark for computer vision. However, current VQA approaches are unable to adequately handle ...