20 citations · 36 across the 9 of their papers we have counts for
10 papers
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…
Complexity Reduction Study Based on RD Costs Approximation for VVC Intra Partitioning
M. E. A. Kherchouche, F. Galpin, T. Dumas +3
In this paper, a complexity study is conducted for Versatile Video Codec (VVC) intra partitioning to accelerate the exhaustive search involved in Rate-Distortion Optimization (RDO)…
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…
Context-adaptive neural network based prediction for image compression
Thierry Dumas, Aline Roumy, Christine Guillemot
This paper describes a set of neural network architectures, called Prediction Neural Networks Set (PNNS), based on both fully-connected and convolutional neural networks, for intra…
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…