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…
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…
OSLO-IC: On-the-Sphere Learned Omnidirectional Image Compression with Attention Modules and Spatial Context
Paul Wawerek-López, Navid Mahmoudian Bidgoli, Pascal Frossard +2
Developing effective 360-degree (spherical) image compression techniques is crucial for technologies like virtual reality and automated driving. This paper advances the state-of-th…
SMIC: Semantic Multi-Item Compression based on CLIP dictionary
Tom Bachard, Thomas Maugey
Semantic compression, a compression scheme where the distortion metric, typically MSE, is replaced with semantic fidelity metrics, tends to become more and more popular. Most recen…