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20202025
most citedIterative Filter Adaptive Network for Single Image Defocus Deblurring

181 citations · 276 across the 13 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.CV2021★ 1 cited

CTRL-C: Camera calibration TRansformer with Line-Classification

Jinwoo Lee, Hyunsung Go, Hyunjoon Lee +3

Single image camera calibration is the task of estimating the camera parameters from a single input image, such as the vanishing points, focal length, and horizon line. In this wor…

cs.CV2021★ 1 cited

Realistic Image Synthesis with Configurable 3D Scene Layouts

Jaebong Jeong, Janghun Jo, Jingdong Wang +2

Recent conditional image synthesis approaches provide high-quality synthesized images. However, it is still challenging to accurately adjust image contents such as the positions an…

cs.CV2021★ 83 cited

Recurrent Video Deblurring with Blur-Invariant Motion Estimation and Pixel Volumes

Hyeongseok Son, Junyong Lee, Jonghyeop Lee +2

For the success of video deblurring, it is essential to utilize information from neighboring frames. Most state-of-the-art video deblurring methods adopt motion compensation betwee…

cs.CV2021★ 1 cited

Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions

Hyeongseok Son, Junyong Lee, Sunghyun Cho +1

This paper proposes a novel deep learning approach for single image defocus deblurring based on inverse kernels. In a defocused image, the blur shapes are similar among pixels alth…

cs.CV2021★ 3 cited

GAN Inversion for Out-of-Range Images with Geometric Transformations

Kyoungkook Kang, Seongtae Kim, Sunghyun Cho

For successful semantic editing of real images, it is critical for a GAN inversion method to find an in-domain latent code that aligns with the domain of a pre-trained GAN model. U…

cs.CV2021★ 181 cited

Iterative Filter Adaptive Network for Single Image Defocus Deblurring

Junyong Lee, Hyeongseok Son, Jaesung Rim +2

We propose a novel end-to-end learning-based approach for single image defocus deblurring. The proposed approach is equipped with a novel Iterative Filter Adaptive Network (IFAN) t…