Hui Yong Kim — accepted AI-conference papers

2026

Block-based Learned Image Compression without Blocking Artifacts

Jong Wook Kim, Suyong Bahk, TaeHwa Lee, HyunDong Cho, Donghyun Kim, Sung-Chang Lim +2

CVPR 2026

Learned image compression (LIC) outperforms traditional codecs but suffers from excessive peak memory usage when handling high-resolution images. Consequently, block-based LIC has been studied to reduce peak memory and peak computational cost, but it often introduces blocking artifacts that degrade

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2023

Towards Efficient Image Compression Without Autoregressive Models

Muhammad Salman Ali, Yeongwoong Kim, Maryam Qamar, Sung-Chang Lim, Donghyun Kim, Chaoning Zhang +2

NeurIPS 2023poster

Recently, learned image compression (LIC) has garnered increasing interest with its rapidly improving performance surpassing conventional codecs. A key ingredient of LIC is a hyperprior-based entropy model, where the underlying joint probability of the latent image features is modeled as a product o…

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