23 citations · 47 across the 7 of their papers we have counts for
4 papers · 1 filter
CurlingNet: Compositional Learning between Images and Text for Fashion IQ Data
Youngjae Yu, Seunghwan Lee, Yuncheol Choi +1
We present an approach named CurlingNet that can measure the semantic distance of composition of image-text embedding. In order to learn an effective image-text composition for the…
Restore from Restored: Single Image Denoising with Pseudo Clean Image
Seunghwan Lee, Dongkyu Lee, Donghyeon Cho +2
In this study, we propose a simple and effective fine-tuning algorithm called "restore-from-restored", which can greatly enhance the performance of fully pre-trained image denoisin…
Restore from Restored: Video Restoration with Pseudo Clean Video
Seunghwan Lee, Donghyeon Cho, Jiwon Kim +1
In this study, we propose a self-supervised video denoising method called "restore-from-restored." This method fine-tunes a pre-trained network by using a pseudo clean video during…
Self-Supervised Fast Adaptation for Denoising via Meta-Learning
Seunghwan Lee, Donghyeon Cho, Jiwon Kim +1
Under certain statistical assumptions of noise, recent self-supervised approaches for denoising have been introduced to learn network parameters without true clean images, and thes…