| Ntire 2018 challenge on image dehazing: Methods and results C Ancuti, CO Ancuti, R Timofte Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 166 | 2018 |
| Learning-Based Just-Noticeable-Quantization-Distortion Modeling for Perceptual Video Coding S Ki, SH Bae, M Kim, H Ko IEEE Transactions on Image Processing 27 (7), 3178-3193, 2018 | 67 | 2018 |
| A novel just-noticeable-difference-based saliency-channel attention residual network for full-reference image quality predictions S Seo, S Ki, M Kim IEEE Transactions on Circuits and Systems for Video Technology 31 (7), 2602-2616, 2020 | 52* | 2020 |
| Fully end-to-end learning based conditional boundary equilibrium GAN with receptive field sizes enlarged for single ultra-high resolution image dehazing S Ki, H Sim, JS Choi, S Kim, M Kim Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 33 | 2018 |
| High-resolution image dehazing with respect to training losses and receptive field sizes H Sim, S Ki, JS Choi, S Seo, S Kim, M Kim Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 24 | 2018 |
| Learning-Based JND-Directed HDR Video Preprocessing for Perceptually Lossless Compression With HEVC S Ki, J Do, M Kim IEEE Access 8, 228605-228618, 2020 | 12 | 2020 |
| Just-noticeable-quantization-distortion based preprocessing for perceptual video coding S Ki, M Kim, H Ko 2017 IEEE Visual Communications and Image Processing (VCIP), 1-4, 2017 | 8 | 2017 |
| Just noticeable quantization blur model based on the DCT complexity feature of the image S Ki, M Kim Proceedings of the Korean Society of Broadcast Engineers Conference, 70-72, 2016 | | 2016 |
| JND based Video Pre-processing Adaptive to Quantization Step sizes for Perceptual Redundancy Reduction S Ki, M Kim Proceedings of the Korean Society of Broadcast Engineers Conference, 100-102, 2016 | | 2016 |
