306 citations
- Centre National de la Recherche ScientifiqueFR50 papers
- Institut National des Sciences Appliquées de RennesFR39 papers
- Université de RennesFR39 papers
- CentraleSupélecFR18 papers
- Institut national de recherche en sciences et technologies du numériqueFR7 papers
- Institut de Recherche Technologique B-comFR6 papers
- Orange (France)FR6 papers
- Merck Serono S.A.S. (France)FR5 papers
- SupélecFR4 papers
- Université Européenne de BretagneFR4 papers
- Centre Inria de l'Université Grenoble AlpesFR3 papers
- Chalmers University of TechnologySE3 papers
8 papers · 1 filter
Cool-chic video: Learned video coding with 800 parameters
Thomas Leguay, Théo Ladune, Pierrick Philippe +1
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 co…
Transformer based Models for Unsupervised Anomaly Segmentation in Brain MR Images
Ahmed Ghorbel, Ahmed Aldahdooh, Shadi Albarqouni +1
The quality of patient care associated with diagnostic radiology is proportionate to a physician workload. Segmentation is a fundamental limiting precursor to both diagnostic and t…
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-…
Lightweight Hardware Transform Design for the Versatile Video Coding 4K ASIC Decoders
Ibrahim Farhat, Wassim Hamidouche, Adrien Grill +2
Versatile Video Coding (VVC) is the next generation video coding standard finalized in July 2020. VVC introduces new coding tools enhancing the coding efficiency compared to its pr…
Coding Standards as Anchors for the CVPR CLIC video track
Théo Ladune, Pierrick Philippe
In 2021, a new track has been initiated in the Challenge for Learned Image Compression~: the video track. This category proposes to explore technologies for the compression of shor…
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…