3 citations · 5 across the 10 of their papers we have counts for
8 papers · 1 filter
Improved Encoding for Overfitted Video Codecs
Thomas Leguay, Théo Ladune, Pierrick Philippe +1
Overfitted neural video codecs offer a decoding complexity orders of magnitude smaller than their autoencoder counterparts. Yet, this low complexity comes at the cost of limited co…
Low-complexity Overfitted Neural Image Codec
Thomas Leguay, Théo Ladune, Pierrick Philippe +2
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 deco…
CAESR: Conditional Autoencoder and Super-Resolution for Learned Spatial Scalability
Charles Bonnineau, Wassim Hamidouche, Jean-François Travers +3
In this paper, we present CAESR, an hybrid learning-based coding approach for spatial scalability based on the versatile video coding (VVC) standard. Our framework considers a low-…
Light Field Image Coding Using VVC standard and View Synthesis based on Dual Discriminator GAN
Nader Bakir, Wassim Hamidouche, Sid Ahmed Fezza +2
Light field (LF) technology is considered as a promising way for providing a high-quality virtual reality (VR) content. However, such an imaging technology produces a large amount…
Binary Probability Model for Learning Based Image Compression
Théo Ladune, Pierrick Philippe, Wassim Hamidouche +2
In this paper, we propose to enhance learned image compression systems with a richer probability model for the latent variables. Previous works model the latents with a Gaussian or…
Extending 2D Saliency Models for Head Movement Prediction in 360-degree Images using CNN-based Fusion
Ibrahim Djemai, Sid Fezza, Wassim Hamidouche +1
Saliency prediction can be of great benefit for 360-degree image/video applications, including compression, streaming , rendering and viewpoint guidance. It is therefore quite natu…