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In this paper, we aim to propose a learning-based image downscaling model, FastDownscaler, which can efficiently produce low-resolution (LR) images that not ...
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ABSTRACT. Image downscaling has been a classical problem and has recently been linked to super-resolution (SR). In this pa-.
In this paper, we aim to propose a learning-based image downscaling model, FastDownscaler, which can efficiently produce low-resolution (LR) images that not ...
Nov 22, 2009 · So my question, is there a perceptually motivated image down-sampling algorithm (or implementation)?. edit: While I am aware of a number of ...
Missing: Restorable Real-
This work formulate image downscaling as an optimization problem where the difference between the input and output images is measured using a widely adopted ...
Sep 28, 2023 · This section describes our image downscaling approach and method, which combines the strength of both content-independent and content-aware ...
Missing: Restorable | Show results with:Restorable
This paper proposes an auto-encoder-based framework that enables joint learning of the downscaling network and the upsc scaling network to maximize the ...
We propose a perceptually based method for downscaling images that provides a better apparent depiction of the input image. We formulate image downscaling ...
The approach limits the sampling space per the content-independent strategy, adaptively relocating such sampled pixel points, and amplifying their intensities ...
Abstract: We propose a perceptually based method for downscaling images that provides a better apparent depiction of the input image.
Missing: Restorable | Show results with:Restorable