Litcius/Paper detail

MobileCodec

Hoang Le, Liang Zhang, Amir Said, Guillaume Sautière, Yang Yang, Pranav Shrestha, Fei Yin, Reza Pourreza, Auke Wiggers

202231 citationsDOIOpen Access PDF

Abstract

Realizing the potential of neural codecs on real-world mobile devices is a big technological challenge due to the inherent conflict between the computational complexity of deep networks and the power-constrained mobile hardware performance. We demonstrate practical feasibility by leveraging Qualcomm's innovation and technology, bridging the gap from neural network-based model simulations to operation on a mobile device powered by Snapdragon® technology. We show the first-ever inter-frame neural video decoder running on a commercial mobile phone, decompressing high-definition videos in real-time while maintaining a low bitrate and high visual quality, comparable to conventional codecs.

Topics & Concepts

Computer scienceCodecBridging (networking)Mobile phoneArtificial neural networkMobile deviceFrame (networking)Real-time computingArtificial intelligenceTelecommunicationsComputer networkOperating systemVideo Coding and Compression TechnologiesAdvanced Data Compression TechniquesImage and Video Quality Assessment
MobileCodec | Litcius