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20192022
most citedPatch-wise Contrastive Style Learning for Instagram Filter Removal

2 citations · 4 across the 4 of their papers we have counts for

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7 papers · 1 filter

cs.CV20221 cited

Modeling the Lighting in Scenes as Style for Auto White-Balance Correction

Furkan Kınlı, Doğa Yılmaz, Barış Özcan +1

Style may refer to different concepts (e.g. painting style, hairstyle, texture, color, filter, etc.) depending on how the feature space is formed. In this work, we propose a novel…

cs.CV2022

Reversing Image Signal Processors by Reverse Style Transferring

Furkan Kınlı, Barış Özcan, Furkan Kıraç

RAW image datasets are more suitable than the standard RGB image datasets for the ill-posed inverse problems in low-level vision, but not common in the literature. There are also a…

cs.CV20222 cited

Patch-wise Contrastive Style Learning for Instagram Filter Removal

Furkan Kınlı, Barış Özcan, Furkan Kıraç

Image-level corruptions and perturbations degrade the performance of CNNs on different downstream vision tasks. Social media filters are one of the most common resources of various…

cs.CV20211 cited

Instagram Filter Removal on Fashionable Images

Furkan Kınlı, Barış Özcan, Furkan Kıraç

Social media images are generally transformed by filtering to obtain aesthetically more pleasing appearances. However, CNNs generally fail to interpret both the image and its filte…

cs.CV2020

A Benchmark for Inpainting of Clothing Images with Irregular Holes

Furkan Kınlı, Barış Özcan, Furkan Kıraç

Fashion image understanding is an active research field with a large number of practical applications for the industry. Despite its practical impacts on intelligent fashion analysi…

cs.CV2020

Quaternion Capsule Networks

Barış Özcan, Furkan Kınlı, Furkan Kıraç

Capsules are grouping of neurons that allow to represent sophisticated information of a visual entity such as pose and features. In the view of this property, Capsule Networks outp…