activity
20162020
most citedAIM 2020 Challenge on Video Temporal Super-Resolution

7 citations · 8 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV20207 cited

AIM 2020 Challenge on Video Temporal Super-Resolution

Sanghyun Son, Jaerin Lee, Seungjun Nah +2

Videos in the real-world contain various dynamics and motions that may look unnaturally discontinuous in time when the recordedframe rate is low. This paper reports the second AIM…

cs.CV2020

NTIRE 2020 Challenge on Image and Video Deblurring

Seungjun Nah, Sanghyun Son, Radu Timofte +1

Motion blur is one of the most common degradation artifacts in dynamic scene photography. This paper reviews the NTIRE 2020 Challenge on Image and Video Deblurring. In this challen…

cs.CV20201 cited

AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results

Seungjun Nah, Sanghyun Son, Radu Timofte +1

Videos contain various types and strengths of motions that may look unnaturally discontinuous in time when the recorded frame rate is low. This paper reviews the first AIM challeng…

cs.CV2017

Enhanced Deep Residual Networks for Single Image Super-Resolution

Bee Lim, Sanghyun Son, Heewon Kim +2

Recent research on super-resolution has progressed with the development of deep convolutional neural networks (DCNN). In particular, residual learning techniques exhibit improved p…

cs.CV2016

Dynamic Scene Deblurring using a Locally Adaptive Linear Blur Model

Tae Hyun Kim, Seungjun Nah, Kyoung Mu Lee

State-of-the-art video deblurring methods cannot handle blurry videos recorded in dynamic scenes, since they are built under a strong assumption that the captured scenes are static…