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Asymmetric Gained Deep Image Compression With Continuous Rate Adaptation
[article]
2022
arXiv
pre-print
With the development of deep learning techniques, the combination of deep learning with image compression has drawn lots of attention. Recently, learned image compression methods had exceeded their classical counterparts in terms of rate-distortion performance. However, continuous rate adaptation remains an open question. Some learned image compression methods use multiple networks for multiple rates, while others use one single model at the expense of computational complexity increase and
arXiv:2003.02012v3
fatcat:wjr66j6ggrhyhigrecw5al4bbi