English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Super Resolution is the problem of recovering a high-resolution image from asingle or multiple low-resolution images of the same scene. It is an ill-posedproblem since high frequency visual details of the scene are completely lost inlow-resolution images. To overcome this, many machine learning approaches havebeen proposed aiming at training a model to recover the lost details in the newscenes. Such approaches include the recent successful effort in utilizing deeplearning techniques to solve super resolution problem. As proven, data itselfplays a significant role in the machine learning process especially deeplearning approaches which are data hungry. Therefore, to solve the problem, theprocess of gathering data and its formation could be equally as vital as themachine learning technique used. Herein, we are proposing a new dataacquisition technique for gathering real image data set which could be used asan input for super resolution, noise cancellation and quality enhancementtechniques. We use a beam-splitter to capture the same scene by a lowresolution camera and a high resolution camera. Since we also release the rawimages, this large-scale dataset could be used for other tasks such as ISPgeneration. Unlike current small-scale dataset used for these tasks, ourproposed dataset includes 11,421 pairs of low-resolution high-resolution imagesof diverse scenes. To our knowledge this is the most complete dataset for superresolution, ISP and image quality enhancement. The benchmarking result showshow the new dataset can be successfully used to significantly improve thequality of real-world image super resolution.

ImagePairs: Realistic Super Resolution Dataset via Beam Splitter Camera Rig