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Found 7 papers, 2 papers with code
Point Cloud Geometry Scalable Coding Using a Resolution and Quality-conditioned Latents Probability Estimator
Experimental results obtained by integrating SRQH in the emerging JPEG Pleno learning-based PC coding standard show that SRQH allows decoding the PC at different qualities and resolutions with a single bitstream while incurring only in a limited RD penalty and increment in complexity w. r. t.
Effectiveness of learning-based image codecs on fingerprint storage
Experimental results show that at a fixed rate point, learned solutions considerably outperform previous fingerprint coding standards, like JPEG2000, both in terms of distortion and minutiae preservation.
Fingerprint Membership and Identity Inference Against Generative Adversarial Networks
Generative models are gaining significant attention as potential catalysts for a novel industrial revolution.
Point Cloud Geometry Scalable Coding with a Quality-Conditioned Latents Probability Estimator
The widespread usage of point clouds (PC) for immersive visual applications has resulted in the use of very heterogeneous receiving conditions and devices, notably in terms of network, hardware, and display capabilities.
Enhancing the Rate-Distortion-Perception Flexibility of Learned Image Codecs with Conditional Diffusion Decoders
Learned image compression codecs have recently achieved impressive compression performances surpassing the most efficient image coding architectures.
All-for-One and One-For-All: Deep learning-based feature fusion for Synthetic Speech Detection
Recent advances in deep learning and computer vision have made the synthesis and counterfeiting of multimedia content more accessible than ever, leading to possible threats and dangers from malicious users.
The Sound of Silence: Efficiency of First Digit Features in Synthetic Audio Detection
The recent integration of generative neural strategies and audio processing techniques have fostered the widespread of synthetic speech synthesis or transformation algorithms.
