Search Results for author: Joonyoung Song

Found 5 papers, 2 papers with code

Federated Contrastive Learning for Privacy-Preserving Unpaired Image-to-Image Translation

no code implementations29 Sep 2021 Joonyoung Song, Jong Chul Ye

In addition, by combining it with the pre-trained VGG network, the learnable part of the discriminator can be further reduced without impairing the image quality, resulting in two order magnitude reduction in the communication cost.

Contrastive Learning Privacy Preserving +2

Federated CycleGAN for Privacy-Preserving Image-to-Image Translation

no code implementations17 Jun 2021 Joonyoung Song, Jong Chul Ye

Although the recent federated learning (FL) allows a neural network to be trained without data exchange, the basic assumption of the FL is that all clients have their own training data from a similar domain, which is different from our image-to-image translation scenario in which each client has images from its unique domain and the goal is to learn image translation between different domains without accessing the target domain data.

Federated Learning Privacy Preserving +2

PyNET-CA: Enhanced PyNET with Channel Attention for End-to-End Mobile Image Signal Processing

1 code implementation7 Apr 2021 Byung-Hoon Kim, Joonyoung Song, Jong Chul Ye, JaeHyun Baek

Reconstructing RGB image from RAW data obtained with a mobile device is related to a number of image signal processing (ISP) tasks, such as demosaicing, denoising, etc.

Demosaicking Denoising

Unsupervised Denoising for Satellite Imagery using Wavelet Subband CycleGAN

no code implementations23 Feb 2020 Joonyoung Song, Jae-Heon Jeong, Dae-Soon Park, Hyun-Ho Kim, Doo-Chun Seo, Jong Chul Ye

Recently, deep learning approaches have been extensively explored for the removal of noises in satellite imagery.


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