Results 21 to 30 of about 3,028,783 (361)
Explorable Super Resolution [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 Single image super resolution (SR) has seen major performance leaps in recent years. However, existing methods do not allow exploring the infinitely many plausible reconstructions that might have given rise to the observed low-resolution (LR) image. These different explanations to the LR image may dramatically vary in their textures and fine details ...
Yuval Bahat, Tomer Michaeli
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Enhanced Deep Residual Networks for Single Image Super-Resolution [PDF]
2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2017 Recent research on super-resolution has progressed with the development of deep convolutional neural networks (DCNN). In particular, residual learning techniques exhibit improved performance.
Bee Lim +4 more
semanticscholar +1 more source
ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting [PDF]
Neural Information Processing Systems, 2023 Diffusion-based image super-resolution (SR) methods are mainly limited by the low inference speed due to the requirements of hundreds or even thousands of sampling steps.
Zongsheng Yue +2 more
semanticscholar +1 more source
Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized Stylization [PDF]
European Conference on Computer Vision, 2023 Diffusion models have demonstrated impressive performance in various image generation, editing, enhancement and translation tasks. In particular, the pre-trained text-to-image stable diffusion models provide a potential solution to the challenging ...
Tao Yang +3 more
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Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network [PDF]
Computer Vision and Pattern Recognition, 2016 Despite the breakthroughs in accuracy and speed of single image super-resolution using faster and deeper convolutional neural networks, one central problem remains largely unsolved: how do we recover the finer texture details when we super-resolve at ...
C. Ledig +8 more
semanticscholar +1 more source
SinSR: Diffusion-Based Image Super-Resolution in a Single Step [PDF]
Computer Vision and Pattern Recognition, 2023 While super-resolution (SR) methods based on diffusion models exhibit promising results, their practical application is hindered by the substantial number of required inference steps.
Yufei Wang +9 more
semanticscholar +1 more source
Nature Communications, 2021 The trans-Golgi network (TGN) serves as a platform to sort and transport proteins to their final destinations. Here the authors show that the TGN of Arabidopsis consists of spatially and temporally distinct subregions and propose that these zones may ...
Yutaro Shimizu +12 more
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eLife, 2023 Although budding yeast has been extensively used as a model organism for studying organelle functions and intracellular vesicle trafficking, whether it possesses an independent endocytic early/sorting compartment that sorts endocytic cargos to the endo ...
Junko Y Toshima +6 more
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Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network [PDF]
Computer Vision and Pattern Recognition, 2016 Recently, several models based on deep neural networks have achieved great success in terms of both reconstruction accuracy and computational performance for single image super-resolution. In these methods, the low resolution (LR) input image is upscaled
Wenzhe Shi +7 more
semanticscholar +1 more source
Bio-Protocol, 2020 Many questions in cell biology can be solved by state-of-the-art technology of live cell imaging. One good example is the mechanism of membrane traffic, in which small membrane carriers are rapidly moving around in the cytoplasm to deliver cargo proteins
Kazuo Kurokawa, Akihiko Nakano
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