White Paper

End to end video super resolution using generative modeling

September 25, 2020

A modern approach to learning for video compression

At present the world is moving towards the next generation 5G networks. With the advent of 5G communication, internet traﬃc has reached its apex. As per 2019 Global Internet Phenomena Report , video data accounts for over 60 percent of downstream traﬃc on the internet and it is increasing day by day. Video has become one of the most commonly used multimedia in our daily life and as High Deﬁnition (HD) and Ultra-High Deﬁnition (UHD) display devices are gaining more attention. This facilitates the need for higher data-rates and greater spectral eﬃciency.

A problem with the video decompression is that we need to take care of temporal features between frames to achieve good decompression rate. We designed a new approach to handle this problems where we propose a new compressed learning network which could learn both the temporal and spatial features quickly and reconstruct and increase their resolution simultaneously.

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