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• W3129120566 abstract "Increasing model size often results in improved performance on super-resolution reconstruction. However, at some point large model cannot SR huge images due to GPU/TPU memory limitations. In this paper, to address this problem, we present Block-Reconstruction(BR) strategy to improve the reconstruction quality of large images, which lower memory consumption. Meanwhile, we propose an enhanced adaptive dense connection super resolution reconstruction network(EDCSR) that has 89M parameters. In AIM2020 Real Image Super-Resolution Challenge, we won the second place in Track 1 and Track 2, and the third place in Track 3." @default.
• W3129120566 created "2021-02-15" @default.
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• W3129120566 date "2020-01-01" @default.
• W3129120566 modified "2023-09-23" @default.
• W3129120566 title "Enhanced Adaptive Dense Connection Single Image Super-Resolution" @default.
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• W3129120566 doi "https://doi.org/10.1007/978-3-030-67070-2_26" @default.
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