most citedRecurrent Video Deblurring with Blur-Invariant Motion Estimation and Pixel Volumes

83 citations · 92 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20211 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.CV20211 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.CV202183 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.CV20211 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.CV20213 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.CV20203 cited

URIE: Universal Image Enhancement for Visual Recognition in the Wild

Taeyoung Son, Juwon Kang, Namyup Kim +2

Despite the great advances in visual recognition, it has been witnessed that recognition models trained on clean images of common datasets are not robust against distorted images i…