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- W2987318324 abstract "This work investigates a distortion scalable learned image encoder that, differently from other works, only encodes those most prominent feature maps that are found to benefit rate-distortion performance. This way, better suiting the texture complexity of content being coded and providing a competitive distortion scalable solution. Experimental results show that the proposed solution performs comparably to HEVC Intra with respect to the perceptually-inspired structural similarity (SSIM) index while being able to be optimized to suit a particular application." @default.
- W2987318324 created "2019-11-22" @default.
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- W2987318324 date "2019-09-01" @default.
- W2987318324 modified "2023-09-23" @default.
- W2987318324 title "Distortion scalable learned image compression" @default.
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- W2987318324 doi "https://doi.org/10.1109/mmsp.2019.8901769" @default.
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