8 citations · 11 across the 3 of their papers we have counts for
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cs.CV2022★ 8 cited
Enriched CNN-Transformer Feature Aggregation Networks for Super-Resolution
Jinsu Yoo, Taehoon Kim, Sihaeng Lee +3
Recent transformer-based super-resolution (SR) methods have achieved promising results against conventional CNN-based methods. However, these approaches suffer from essential short…
cs.CV2021
Self-Supervised Adaptation for Video Super-Resolution
Jinsu Yoo, Tae Hyun Kim
Recent single-image super-resolution (SISR) networks, which can adapt their network parameters to specific input images, have shown promising results by exploiting the information…
cs.CV2020
Fast Adaptation to Super-Resolution Networks via Meta-Learning
Seobin Park, Jinsu Yoo, Donghyeon Cho +2
Conventional supervised super-resolution (SR) approaches are trained with massive external SR datasets but fail to exploit desirable properties of the given test image. On the othe…