City University of Hong Kong

Linwei Zhu

Yun Zhang

Sam Tak Wu Kwong

Systems and methods which provide Generative Adversarial Network (GAN) based intra prediction for video coding are described. GAN based intra prediction as implemented according to embodiments may be modeled as an inpainting task. For example, intra prediction may be formulated as a learning based inpainting task, wherein a latent variable is designed to control different generation modes. GAN based intra prediction provided according to embodiments of the invention may be implemented alone or in combination with one or more other video compression technique, such as a direction intra prediction technique. The intra prediction module of such a HEVC encoder/decoder may be redesigned to also apply GAN based inpainting in intra prediction, wherein Rate-Distortion Optimization (RDO) may be performed to select the best intra prediction mode between the intra prediction approaches.

Generative adversarial network based intra prediction for video coding

Systems and methods which provide Convolutional Neural Network (CNN) based synthesized view quality enhancement for video coding are described. Embodiments may comprise an encoder configured for CNN based synthesized view quality enhancement configured to provide improved coding efficiency while maintaining synthesized view quality. Additionally or alternatively, embodiments may comprise a virtual viewpoint generator configured for CNN based synthesized view quality enhancement configured provide post-processing of the synthesized view at the decoder side to reduce the artifacts. CNN based synthesized view quality enhancement may, for example, be provided for 3D video coding to improve its coding efficiency, which can be utilized in 3D scenarios, such as 3DTV.

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Hong Kong, China

Linwei Zhu