29 citations · 115 across the 20 of their papers we have counts for
4 papers · 1 filter
Discovering shared interpretable operations in image compression autoencoders
Caroline Mazini Rodrigues, Nicolas Keriven, Thomas Maugey
With the increasing adoption of deep learning for applications such as image compression, improvements in the rate-distortion trade-off have been achieved at the cost of increasing…
A Projection-Based Surrogate Gradient Interpretation for Neural Codec Wrappers
Esteban Pesnel, Julien Le Tanou, Michael Ropert +2
Neural wrappers are learned pre-and postprocessing networks designed to enhance the performance of conventional video codecs. Although these approaches can significantly improve co…
SCALED : Surrogate-gradient for Codec-Aware Learning of Downsampling in ABR Streaming
Esteban Pesnel, Julien Le Tanou, Michael Ropert +2
The rapid growth in video consumption has introduced significant challenges to modern streaming architectures. Over-the-Top (OTT) video delivery now predominantly relies on Adaptiv…
Efficient training for compact compression models via sequential distillation
Caroline Mazini Rodrigues, Nicolas Keriven, Thomas Maugey
Deep learning models for image compression often face practical limitations in hardware-constrained applications. Although these models achieve high-quality reconstructions, they a…