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20162022
most citedAIM 2020 Challenge on Video Temporal Super-Resolution

7 citations · 11 across the 4 of their papers we have counts for

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8 papers · 1 filter

cs.CV20221 cited

Pay Attention to Hidden States for Video Deblurring: Ping-Pong Recurrent Neural Networks and Selective Non-Local Attention

JoonKyu Park, Seungjun Nah, Kyoung Mu Lee

Video deblurring models exploit information in the neighboring frames to remove blur caused by the motion of the camera and the objects. Recurrent Neural Networks~(RNNs) are often…

cs.CV2021

NTIRE 2021 Challenge on Video Super-Resolution

Sanghyun Son, Suyoung Lee, Seungjun Nah +2

Super-Resolution (SR) is a fundamental computer vision task that aims to obtain a high-resolution clean image from the given low-resolution counterpart. This paper reviews the NTIR…

cs.CV2021

NTIRE 2021 Challenge on Image Deblurring

Seungjun Nah, Sanghyun Son, Suyoung Lee +2

Motion blur is a common photography artifact in dynamic environments that typically comes jointly with the other types of degradation. This paper reviews the NTIRE 2021 Challenge o…

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…