Reading: Double-Input CNN — Mean-based Mask (MM)+Add-based Fusion (AF) (Codec Filtering)

Original article was published on Artificial Intelligence on Medium

Reading: Double-Input CNN — Mean-based Mask (MM)+Add-based Fusion (AF) (Codec Filtering)

In this story, Enhancing HEVC Compressed Videos with a Partition-masked Convolutional Neural Network (Double-Input CNN), by Shanghai Jiao Tong University, and University of Maryland, is described. I read this because I work on video coding research. (The name, Double-Input CNN, is named by another paper. Thus, I also call it Double-Input CNN here.)

In contrast to existing CNN-based approaches, which only take the decoded frame as the input to the CNN, the proposed approach considers the coding unit (CU) size information and combines it with the distorted decoded frame as input such that the degradation introduced by HEVC is reduced more efficiently. This is a paper in 2018 ICIP. Sik-Ho Tsang @ Medium)