Abstract

Motion blur is one of the most common artifacts in photographs and videos. Handshaken mobile cameras and motions of objects occurring during the exposure are the main cause of the blur. While sharp scenes can be captured from fast shutter speed, an aligned pair of blurry and sharp images are hard to be captured at the same time. To enable supervised learning for deblurring, we propose a way to synthesize dynamic motion blurred images from high speed cameras to construct large-scale dataset. We show deep neural networks trained on this data generalizes to real blurry images and videos. Finally, we present a high-quality REDS dataset for video deblurring and super-resolution. The REDS dataset is in high-quality in terms of the reference frames and the realism of quality degradation. The REDS dataset was employed in the NTIRE 2019 challenges on video deblurring and super-resolution.

About Seungjun Nah

Seungjun Nah is a Ph. D. student at Seoul National University, advised by Prof. Kyoung Mu Lee. He received his BS degree from Seoul National University in 2014. He has worked on computer vision research topics including deblurring, super-resolution, and neural network acceleration. He won the 1st place award from NTIRE 2017 super-resolution challenge and workshop. He co-organized the NTIRE 2019  and AIM 2019 workshops and challenges on video quality restoration. He has reviewed conference (ICCV 2019, CVPR 2018, SIGGRAPH Asia 2018) and journal (IJCV, TNNLS, TMM, TIP) paper submissions. He is one of the best reviewers in ICCV 2019. His research interests include visual quality enhancement, low-level computer vision, and efficient deep learning. He is currently a guest scientist at Max Planck Institute for Intelligent Systems.

References

[1] Seungjun Nah, Tae Hyun Kim, and Kyoung Mu Lee, "Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring," CVPR 2017

[2] Seungjun Nah, Sanghyun Son, and Kyoung Mu Lee, “Recurrent Neural Networks with Intra-Frame Iterations for Video Deblurring,” CVPR 2019

[3] Seungjun Nah, Sungyong Baik, Seokil Hong, Gyeongsik Moon, Sanghyun Son, Radu Timofte, and Kyoung Mu Lee, “NTIRE 2019 Challenge on Video Deblurring and Super-Resolution: Dataset and Study,” CVPRW 2019