Just-noticeable-quantization-distortion based preprocessing for perceptual video coding. - Sehwan Ki; Munchurl Kim; Hyunsuk Ko (VCIP, 2017)

Fully End-to-End Learning Based Conditional Boundary Equilibrium GAN With Receptive Field Sizes Enlarged for Single Ultra-High Resolution Image Dehazing. - Sehwan Ki; Hyeonjun Sim; Jae-Seok Choi; Saehun Kim; Munchurl Kim (CVPR Workshops, 2018)

High-Resolution Image Dehazing With Respect to Training Losses and Receptive Field Sizes. - Hyeonjun Sim; Sehwan Ki; Jae-Seok Choi; Soomin Seo; Saehun Kim; Munchurl Kim (CVPR Workshops, 2018)

Learning-Based Just-Noticeable-Quantization- Distortion Modeling for Perceptual Video Coding. - Sehwan Ki; Sung-Ho Bae; Munchurl Kim; Hyunsuk Ko (IEEE Trans. Image Process., 2018)

Deep HVS-IQA Net: Human Visual System Inspired Deep Image Quality Assessment Networks. - Soomin Seo; Sehwan Ki; Munchurl Kim (CoRR, 2019)

Learning-Based JND-Directed HDR Video Preprocessing for Perceptually Lossless Compression With HEVC. - Sehwan Ki; Jeonghyeok Do; Munchurl Kim (IEEE Access, 2020)

A Novel Just-Noticeable-Difference-Based Saliency-Channel Attention Residual Network for Full-Reference Image Quality Predictions. - Soomin Seo; Sehwan Ki; Munchurl Kim (IEEE Trans. Circuits Syst. Video Technol., 2021)

ATTIQA: Generalizable Image Quality Feature Extractor Using Attribute-Aware Pretraining. - Daekyu Kwon; Dongyoung Kim; Sehwan Ki; Younghyun Jo; Hyong-Euk Lee; Seon Joo Kim (ACCV (4), 2022)

Information-Theoretic GAN Compression with Variational Energy-based Model. - Minsoo Kang; Hyewon Yoo; Eunhee Kang; Sehwan Ki; Hyong-Euk Lee; Bohyung Han (NeurIPS, 2022)

CLIP-Guided Attribute Aware Pretraining for Generalizable Image Quality Assessment. - Daekyu Kwon; Dongyoung Kim; Sehwan Ki; Younghyun Jo; Hyong-Euk Lee; Seon Joo Kim (CoRR, 2024)