Learned image and video compression via autoencoders with spatial-temporal energy compaction penalties outperforms standards on MS-SSIM and visual quality.
Learning Con- volutional Networks for Content-weighted Image Compres- sion
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A learned image compression system using deep residual learning and sub-pixel convolution reaches 0.972 MS-SSIM at 0.15 bits per pixel in the CLIC validation phase.
citing papers explorer
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Learning Image and Video Compression through Spatial-Temporal Energy Compaction
Learned image and video compression via autoencoders with spatial-temporal energy compaction penalties outperforms standards on MS-SSIM and visual quality.
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Deep Residual Learning for Image Compression
A learned image compression system using deep residual learning and sub-pixel convolution reaches 0.972 MS-SSIM at 0.15 bits per pixel in the CLIC validation phase.