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Published in 2024 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2024.3383862
Abstract: Burst denoising aims to generate a clean image based on a sequence of noisy frames of the same scene captured in quick succession. However, relative motions inevitably happen between frames due to the movements of…
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Keywords:
kernel prediction;
optical flow;
burst denoising;
ebdnet integrating ... See more keywords
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Published in 2021 at "Computer Graphics Forum"
DOI: 10.1111/cgf.14338
Abstract: Real‐time Monte Carlo denoising aims at removing severe noise under low samples per pixel (spp) in a strict time budget. Recently, kernel‐prediction methods use a neural network to predict each pixel's filtering kernel and have…
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Keywords:
monte carlo;
time;
real time;
kernel prediction ... See more keywords
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Published in 2021 at "Journal of Electronic Imaging"
DOI: 10.1117/1.jei.30.2.023021
Abstract: Abstract. Deep convolutional neural networks (CNNs) have achieved considerable success in terms of image denoising. However, previous CNN denoisers have been restricted by rigid kernel convolution that applies equal spatial treatment across images. To fully…
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Keywords:
prediction network;
single image;
image;
kernel prediction ... See more keywords
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Published in 2022 at "Symmetry"
DOI: 10.3390/sym14020395
Abstract: In this paper, we present a denoising network composed of a kernel prediction network and a deep generative adversarial network to construct an end-to-end overall network structure. The network structure consists of three parts: the…
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Keywords:
network;
prediction network;
model;
kernel prediction ... See more keywords