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Found 6 papers, 0 papers with code
Fine color guidance in diffusion models and its application to image compression at extremely low bitrates
This study addresses the challenge of, without training or fine-tuning, controlling the global color aspect of images generated with a diffusion model.
OSLO: On-the-Sphere Learning for Omnidirectional images and its application to 360-degree image compression
State-of-the-art 2D image compression schemes rely on the power of convolutional neural networks (CNNs).
Fine granularity access in interactive compression of 360-degree images based on rate-adaptive channel codes
This requires two characteristics: efficient compression of data, to lower the storage cost, and random access ability to extract part of the compressed stream requested by the user (for reducing the transmission rate).
Prediction and Sampling with Local Graph Transforms for Quasi-Lossless Light Field Compression
The proposed approach is investigated and is shown to be very efficient in the context of spatio-angular transforms for quasi-lossless compression of light fields.
Geometry-Aware Graph Transforms for Light Field Compact Representation
Both non separable and separable transforms are considered.
Navigation domain representation for interactive multiview imaging
In this paper, we propose a novel multiview data representation that permits to satisfy bandwidth and storage constraints in an interactive multiview streaming system.
