2021
Checkerboard Context Model for Efficient Learned Image Compression
CVPR 2021poster
For learned image compression, the autoregressive context model is proved effective in improving the rate-distortion (RD) performance. Because it helps remove spatial redundancies among latent representations. However, the decoding process must be done in a strict scan order, which breaks the parall…