1. MobileCodec
- Author
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Le, Hoang, Zhang, Liang, Said, Amir, Sautiere, Guillaume, Yang, Yang, Shrestha, Pranav, Yin, Fei, Pourreza, Reza, and Wiggers, Auke
- Subjects
FOS: Computer and information sciences ,Computer Vision and Pattern Recognition (cs.CV) ,Image and Video Processing (eess.IV) ,Computer Science - Computer Vision and Pattern Recognition ,FOS: Electrical engineering, electronic engineering, information engineering ,Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Multimedia ,Multimedia (cs.MM) - Abstract
Realizing the potential of neural video codecs on mobile devices is a big technological challenge due to the computational complexity of deep networks and the power-constrained mobile hardware. We demonstrate practical feasibility by leveraging Qualcomm's technology and innovation, bridging the gap from neural network-based codec simulations running on wall-powered workstations, to real-time 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, decoding high-definition videos in real-time while maintaining a low bitrate and high visual quality., Comment: ACM MMSys 2022
- Published
- 2022
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