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Autoencoder Architectures for Low-Rate Sparse Point Cloud Geometry Coding

Efficient compression of sparse point cloud geometry remains a critical challenge in 3D content processing, particularly for low-rate scenarios where conventional codecs struggle to maintain efficiency. This work proposes a system-level framework for low-rate sparse geometry coding, leveraging three...

Whakaahuatanga katoa

I tiakina i:
Ngā taipitopito rārangi puna kōrero
Ngā kaituhi matua: Ivaylo Bozhilov, Radostina Petkova, Krasimir Tonchev, Agata Manolova, Vladimir Poulkov, H. Vincent Poor
Hōputu: Artigo
Reo:Inglês
I whakaputaina: IEEE 2025-01-01
Rangatū:IEEE Access
Ngā marau:
Urunga tuihono:https://ieeexplore.ieee.org/document/11303733/
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