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Lorenzo Catania, Dario Allegra
Implicit Neural Representations (INRs) have recently emerged as a promising paradigm for image compression, offering a fundamentally different approach from traditional and learned codecs. Nevertheless, INR-based methods for image compression suffer from long encoding times and a consistent performance gap in classic …
Lorenzo Catania, Dario Allegra
Implicit Neural Representations (INRs) have recently emerged as a promising paradigm for image compression, offering a fundamentally different approach from traditional and learned codecs. Nevertheless, INR-based methods for image compression suffer from long encoding times and a consistent performance gap in classic …
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Paolino Trapani, R. Rizza, Dario Allegra, Anna Maria Gueli et autres
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R. Rizza, Simone Pio Barbagallo, Dario Allegra, Anna Maria Gueli et autres
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Gioele Litrico, Dario Allegra, Anna Maria Gueli, Filippo Stanco
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R. Rizza, Paolino Trapani, Myriam Vaccaro, Dario Allegra et autres
Cultural heritage, in all its tangible and intangible expressions, is undergoing a process of renewal driven by the integration of digital technologies and participatory approaches. This study presents a pilot project developed within the SAMOTHRACE Fundation, focused on the design of a …
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Gioele Litrico, Dario Allegra, Anna Maria Gueli, F. Stanco
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Simone Pio Barbagallo, R. Rizza, Dario Allegra, Anna Maria Gueli et autres
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Lorenzo Catania, Dario Allegra
Implicit Neural Representations (INRs) have recently proven to be effective in data compression tasks, offering an alternative to complex hand-crafted encoding and decoding pipelines. However, INR-based methods for image compression suffer from long encoding times and a consistent performance gap in classic …
it (code pays fourni par la source)
Lorenzo Catania, Dario Allegra, Luigi Capogrosso, Thu Nguyen
In this companion paper, we reproduce the experiments presented in our work titled ''NIF: A Fast Implicit Image Compression with Bottleneck Layers and Modulated Sinusoidal Activations'' [2], presented at ACM Multimedia 2023. In this study, we present the architecture and the technical …
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Andrea Di Pierno, Luca Guarnera, Dario Allegra, Sebastiano Battiato
The proliferation of audio deepfakes poses a growing threat to trust in digital communications. While detection methods have advanced, attributing audio deepfakes to their source models remains an underexplored yet crucial challenge. In this paper we introduce LAVA (Layered Architecture for Voice …
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Claudio Vittorio Ragaglia, Lorenzo Catania, Francesco Guarnera, Dario Allegra et autres
We explore whether the latent space of the recent JPEG AI compression standard can be employed for high-level semantic tasks. Specifically, we propose a decoding-free approach to image-to-image retrieval and deepfake generator attribution that operates directly on JPEG AI latents, using simple …
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