54 citations · 59 across the 10 of their papers we have counts for
5 papers · 1 filter
Image-Difficulty-Aware Evaluation of Super-Resolution Models
Atakan Topaloglu, Ahmet Bilican, Cansu Korkmaz +1
Image super-resolution models are commonly evaluated by average scores (over some benchmark test sets), which fail to reflect the performance of these models on images of varying d…
Leveraging Vision-Language Models to Select Trustworthy Super-Resolution Samples Generated by Diffusion Models
Cansu Korkmaz, Ahmet Murat Tekalp, Zafer Dogan
Super-resolution (SR) is an ill-posed inverse problem with many feasible solutions consistent with a given low-resolution image. On one hand, regressive SR models aim to balance fi…
NTIRE 2024 Challenge on Image Super-Resolution (x4): Methods and Results
Zheng Chen, Zongwei Wu, Eduard Zamfir +85
This paper reviews the NTIRE 2024 challenge on image super-resolution (4), highlighting the solutions proposed and the outcomes obtained. The challenge involves generating…
MMSR: Multiple-Model Learned Image Super-Resolution Benefiting From Class-Specific Image Priors
Cansu Korkmaz, A. Murat Tekalp, Zafer Dogan
Assuming a known degradation model, the performance of a learned image super-resolution (SR) model depends on how well the variety of image characteristics within the training set…
Perception-Distortion Trade-off in the SR Space Spanned by Flow Models
Cansu Korkmaz, A. Murat Tekalp, Zafer Dogan +2
Flow-based generative super-resolution (SR) models learn to produce a diverse set of feasible SR solutions, called the SR space. Diversity of SR solutions increases with the temper…