Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Leguay, Thomas"'
Autor:
Philippe, Pierrick, Ladune, Théo, Clare, Gordon, Henry, Félix, Blard, Théophile, Leguay, Thomas
Neural image compression, based on auto-encoders and overfitted representations, relies on a latent representation of the coded signal. This representation needs to be compact and uses low resolution feature maps. In the decoding process, those laten
Externí odkaz:
http://arxiv.org/abs/2411.19249
We propose a lightweight learned video codec with 900 multiplications per decoded pixel and 800 parameters overall. To the best of our knowledge, this is one of the neural video codecs with the lowest decoding complexity. It is built upon the overfit
Externí odkaz:
http://arxiv.org/abs/2402.03179
This paper summarises the design of the Cool-Chic candidate for the Challenge on Learned Image Compression. This candidate attempts to demonstrate that neural coding methods can lead to low complexity and lightweight image decoders while still offeri
Externí odkaz:
http://arxiv.org/abs/2401.02156
This paper summarises the design of the candidate ED for the Challenge on Learned Image Compression 2024. This candidate aims at providing an anchor based on conventional coding technologies to the learning-based approaches mostly targeted in the cha
Externí odkaz:
http://arxiv.org/abs/2401.02145
We propose a neural image codec at reduced complexity which overfits the decoder parameters to each input image. While autoencoders perform up to a million multiplications per decoded pixel, the proposed approach only requires 2300 multiplications pe
Externí odkaz:
http://arxiv.org/abs/2307.12706
We introduce COOL-CHIC, a Coordinate-based Low Complexity Hierarchical Image Codec. It is a learned alternative to autoencoders with 629 parameters and 680 multiplications per decoded pixel. COOL-CHIC offers compression performance close to modern co
Externí odkaz:
http://arxiv.org/abs/2212.05458