In the last two decades, we have witnessed an immense increase in the use of multimedia content on the internet, for multiple applications ranging from the most innocuous to very critical ones. Naturally, this emergence has given rise to many types of threats posed when this content can be...
01a Articolo in rivista
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The increasing demand for edge devices causes the necessity for recent technologies to be adaptable to nonspecialized hardware. In particular, in the context of augmented, virtual reality, and computer graphics, the 3-D object reconstruction task from a sparse point cloud is highly computationally...
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The rapid advancement of deep learning and computer vision technologies has given rise to a concerning class of deceptive media, commonly known as deepfakes. This paper addresses emerging trends in deepfakes, including the creation of hyper-realistic facial manipulations, the incorporation of...
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Deep fake technology paves the way for a new generation of super realistic artificial content. While this opens the door to extraordinary new applications, the malicious use of deepfakes allows for far more realistic disinformation attacks than ever before. In this paper, we start from the...
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Vision Transformer (ViT) architectures are becoming increasingly popular and widely employed to tackle computer vision applications. Their main feature is the capacity to extract global information through the self-attention mechanism, outperforming earlier convolutional neural networks. However,...
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This article delves into the intricate process of artificial intelligence-generated content detection, shedding light on automated detectors' challenges and revealing human detection biases, strengths, and weaknesses.
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Ground-truth RGBD data are fundamental for a wide range of computer vision applications; however, those labeled samples are difficult to collect and time-consuming to produce. A common solution to overcome this lack of data is to employ graphic engines to produce synthetic proxies; however, those...
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With demanding and sophisticated crimes and terrorist threats becoming more pervasive, allied with the advent and widespread of fake news, it becomes paramount to design and develop objective and scientific-based criteria to identify the characteristics of investigated materials associated with...
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A recent trend in binary code analysis promotes the use of neural solutions based on instruction embedding models. An instruction embedding model is a neural network that transforms assembly instructions into embedding vectors. If the embedding network is able to processes sequences of assembly...
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In this article we propose the first multi-task benchmark for evaluating the performances of machine learning models that work on low level assembly functions. While the use of multi-task benchmark is a standard in the natural language processing (NLP) field, such practice is unknown in the field...