9 citations · 20 across the 9 of their papers we have counts for
9 papers
Efficient Cost-and-Quality Controllable Arbitrary-scale Super-resolution with Fourier Constraints
Kazutoshi Akita, Norimichi Ukita
Cost-and-Quality (CQ) controllability in arbitrary-scale super-resolution is crucial. Existing methods predict Fourier components one by one using a recurrent neural network. Howev…
Efficient Burst Super-Resolution with One-step Diffusion
Kento Kawai, Takeru Oba, Kyotaro Tokoro +2
While burst Low-Resolution (LR) images are useful for improving their Super Resolution (SR) image compared to a single LR image, prior burst SR methods are trained in a determinist…
Test-time Cost-and-Quality Controllable Arbitrary-Scale Super-Resolution with Variable Fourier Components
Kazutoshi Akita, Norimichi Ukita
Super-resolution (SR) with arbitrary scale factor and cost-and-quality controllability at test time is essential for various applications. While several arbitrary-scale SR methods…
Burst Super-Resolution with Diffusion Models for Improving Perceptual Quality
Kyotaro Tokoro, Kazutoshi Akita, Norimichi Ukita
While burst LR images are useful for improving the SR image quality compared with a single LR image, prior SR networks accepting the burst LR images are trained in a deterministic…
Kernelized Back-Projection Networks for Blind Super Resolution
Tomoki Yoshida, Yuki Kondo, Takahiro Maeda +2
Since non-blind Super Resolution (SR) fails to super-resolve Low-Resolution (LR) images degraded by arbitrary degradations, SR with the degradation model is required. However, this…
NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results
Goutam Bhat, Martin Danelljan, Radu Timofte +25
This paper reviews the NTIRE2021 challenge on burst super-resolution. Given a RAW noisy burst as input, the task in the challenge was to generate a clean RGB image with 4 times hig…