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20192022
most citedBGGAN: Bokeh-Glass Generative Adversarial Network for Rendering Realistic Bokeh

21 citations · 69 across the 10 of their papers we have counts for

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6 papers · 1 filter

cs.CV20223 cited

AIM 2022 Challenge on Instagram Filter Removal: Methods and Results

Furkan Kınlı, Sami Menteş, Barış Özcan +30

This paper introduces the methods and the results of AIM 2022 challenge on Instagram Filter Removal. Social media filters transform the images by consecutive non-linear operations,…

cs.CV2021

NTIRE 2021 Depth Guided Image Relighting Challenge

Majed El Helou, Ruofan Zhou, Sabine Susstrunk +1

Image relighting is attracting increasing interest due to its various applications. From a research perspective, image relighting can be exploited to conduct both image normalizati…

cs.CV202016 cited

AIM 2020 Challenge on Learned Image Signal Processing Pipeline

Andrey Ignatov, Radu Timofte, Zhilu Zhang +36

This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world RAW-to…

cs.CV202021 cited

BGGAN: Bokeh-Glass Generative Adversarial Network for Rendering Realistic Bokeh

Ming Qian, Congyu Qiao, Jiamin Lin +4

A photo captured with bokeh effect often means objects in focus are sharp while the out-of-focus areas are all blurred. DSLR can easily render this kind of effect naturally. Howeve…

cs.CV2020

NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results

Abdelrahman Abdelhamed, Mahmoud Afifi, Radu Timofte +87

This paper reviews the NTIRE 2020 challenge on real image denoising with focus on the newly introduced dataset, the proposed methods and their results. The challenge is a new versi…

cs.CV20203 cited

NTIRE 2020 Challenge on Image Demoireing: Methods and Results

Shanxin Yuan, Radu Timofte, Ales Leonardis +43

This paper reviews the Challenge on Image Demoireing that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2020. Demo…