Results 11 to 20 of about 1,135,244 (321)
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.
Kim, Heewon +4 more
core +2 more sources
Process of image super-resolution
CoRR, 2020 In this paper we explain a process of super-resolution reconstruction allowing to increase the resolution of an image.The need for high-resolution digital images exists in diverse domains, for example the medical and spatial domains.
Lablanche, Gerard, Lablanche, Sebastien
core +4 more sources
Image Super-Resolution via Iterative Refinement [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 We present SR3, an approach to image Super-Resolution via Repeated Refinement. SR3 adapts denoising diffusion probabilistic models (Ho et al. 2020), (Sohl-Dickstein et al.
Chitwan Saharia +5 more
semanticscholar +1 more source
Super resolution for root imaging [PDF]
Applications in Plant Sciences, 2020 PremiseHigh‐resolution cameras are very helpful for plant phenotyping as their images enable tasks such as target vs. background discrimination and the measurement and analysis of fine above‐ground plant attributes. However, the acquisition of high‐resolution images of plant roots is more challenging than above‐ground data collection.
Jose F. Ruiz‐Munoz +4 more
openaire +4 more sources
Activating More Pixels in Image Super-Resolution Transformer [PDF]
Computer Vision and Pattern Recognition, 2022 Transformer-based methods have shown impressive performance in low-level vision tasks, such as image super-resolution. However, we find that these networks can only utilize a limited spatial range of input information through attribution analysis.
Xiangyu Chen +3 more
semanticscholar +1 more source
Super-resolution Ultrasound Imaging [PDF]
Ultrasound in Medicine & Biology, 2020 Ultrasound in medicine & biology 46(4), 865-891 (2020).
Christensen-Jeffries, Kirsten +11 more
openaire +5 more sources
Super-Resolution Imaging with Graphene [PDF]
Biosensors, 2021 Super-resolution optical imaging is a consistent research hotspot for promoting studies in nanotechnology and biotechnology due to its capability of overcoming the diffraction limit, which is an intrinsic obstacle in pursuing higher resolution for conventional microscopy techniques. In the past few decades, a great number of techniques in this research
Xiaoxiao Jiang +6 more
openaire +3 more sources
Designing a Practical Degradation Model for Deep Blind Image Super-Resolution [PDF]
IEEE International Conference on Computer Vision, 2021 It is widely acknowledged that single image super-resolution (SISR) methods would not perform well if the assumed degradation model deviates from those in real images.
K. Zhang +3 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
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