20 citations · 36 across the 9 of their papers we have counts for
8 papers · 1 filter
Partition Tree Search Acceleration for VVC: Survey and Evaluation with VTM Evolution
M. E. A. Kherchouche, F. Galpin, T. Dumas +2
The Versatile Video Coding (VVC) standard, introduced in 2020, offers 40-50% bitrate savings for equivalent visual quality of reconstructed videos over its predecessor, High Effici…
Enhanced Template-based Intra Mode Derivation with Adaptive Block Vector Replacement
Jiaqi Zhang, Jiaye Fu, Chuanmin Jia +5
Intra prediction is a crucial component in traditional video coding frameworks, aiming to eliminate spatial redundancy within frames. In recent years, an increasing number of decod…
Designs and Implementations in Neural Network-based Video Coding
Yue Li, Junru Li, Chaoyi Lin +9
The past decade has witnessed the huge success of deep learning in well-known artificial intelligence applications such as face recognition, autonomous driving, and large language…
Revisiting the Sample Adaptive Offset post-filter of VVC with Neural-Networks
Philippe Bordes, Franck Galpin, Thierry Dumas +1
The Sample Adaptive Offset (SAO) filter has been introduced in HEVC to reduce general coding and banding artefacts in the reconstructed pictures, in complement to the De-Blocking F…
Neural Network based Inter bi-prediction Blending
Franck Galpin, Philippe Bordes, Thierry Dumas +2
This paper presents a learning-based method to improve bi-prediction in video coding. In conventional video coding solutions, the motion compensation of blocks from already decoded…
Combined neural network-based intra prediction and transform selection
Thierry Dumas, Franck Galpin, Philippe Bordes
The interactions between different tools added successively to a block-based video codec are critical to its rate-distortion efficiency. In particular, when deep neural network-bas…
Iterative training of neural networks for intra prediction
Thierry Dumas, Franck Galpin, Philippe Bordes
This paper presents an iterative training of neural networks for intra prediction in a block-based image and video codec. First, the neural networks are trained on blocks arising f…
Autoencoder based image compression: can the learning be quantization independent?
Thierry Dumas, Aline Roumy, Christine Guillemot
This paper explores the problem of learning transforms for image compression via autoencoders. Usually, the rate-distortion performances of image compression are tuned by varying t…