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NN-VVC: Versatile Video Coding boosted by self-supervisedly learned image coding for machines
To the best of our knowledge, this is the first research paper showing a hybrid video codec that outperforms VVC on multiple datasets and multiple machine vision tasks.
Bridging the gap between image coding for machines and humans
Image coding for machines (ICM) aims at reducing the bitrate required to represent an image while minimizing the drop in machine vision analysis accuracy.
Leveraging progressive model and overfitting for efficient learned image compression
Nevertheless, the proposed LIC systems are still inferior to the state-of-the-art traditional techniques, for example, the Versatile Video Coding (VVC/H. 266) standard, due to either their compression performance or decoding complexity.
Coding of volumetric content with MIV using VVC subpictures
This paper shows the benefit of using subpictures in the MIV use-case.
Omnidirectional MediA Format (OMAF): Toolbox for Virtual Reality Services
OMAF specifies the media format for coding, storage, delivery, and rendering of omnidirectional media, including video, audio, images, and timed text.
Lossless Image Compression Using a Multi-Scale Progressive Statistical Model
Recently, multi-scale autoregressive models have been proposed to address this limitation.
