On Block Prediction For Learning-Based Point Cloud Compression
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Point cloud imaging has emerged as an efficient and popular solution to represent immersive visual information. However, the large volume of data generated in the acquisition process reveals the need of efficient compression solutions in order to store and ...
Recent advancements in acquisition of three-dimensional models have been increasingly drawing attention to imaging modalities based on the plenoptic representations, such as light fields and point clouds. Since point cloud models can often contain millions ...
The growing adoption of point clouds as an imaging modality has stimulated the search for efficient solutions for compression. Learning-based algorithms have been reporting increasingly better performance and are drawing the attention from the research com ...
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