Transfer Learning from Synthetic to Real-Noise Denoising with Adaptive Instance Normalization Y Kim, JW Soh, GY Park, NI Cho Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 200 | 2020 |
Multi-modal text recognition networks: Interactive enhancements between visual and semantic features B Na, Y Kim, S Park European Conference on Computer Vision, 446-463, 2022 | 50 | 2022 |
Synthtiger: Synthetic text image generator towards better text recognition models M Yim, Y Kim, HC Cho, S Park International Conference on Document Analysis and Recognition, 109-124, 2021 | 49 | 2021 |
A pseudo-blind convolutional neural network for the reduction of compression artifacts Y Kim, JW Soh, J Park, B Ahn, HS Lee, YS Moon, NI Cho IEEE Transactions on Circuits and Systems for Video Technology 30 (4), 1121-1135, 2019 | 45 | 2019 |
Convolutional neural networks and training strategies for skin detection Y Kim, I Hwang, NI Cho 2017 IEEE International Conference on Image Processing (ICIP), 3919-3923, 2017 | 35 | 2017 |
Multi-Lingual Optical Character Recognition System Using the Reinforcement Learning of Character Segmenter J Park, E Lee, Y Kim, I Kang, HI Koo, NI Cho IEEE Access 8, 174437-174448, 2020 | 33 | 2020 |
AGARNet: Adaptively Gated JPEG Compression Artifacts Removal Network for a Wide Range Quality Factor Y Kim, JW Soh, NI Cho IEEE Access 8, 20160-20170, 2020 | 32 | 2020 |
Adaptively Tuning a Convolutional Neural Network by Gating Process for Image Denoising Y Kim, JW Soh, NI Cho 2019 IEEE International Conference on Image Processing (ICIP), 2019 | 32 | 2019 |
Adaptively tuning a convolutional neural network by gate process for image denoising Y Kim, JW Soh, NI Cho IEEE Access 7, 63447-63456, 2019 | 32 | 2019 |
Reduction of video compression artifacts based on deep temporal networks JW Soh, J Park, Y Kim, B Ahn, HS Lee, YS Moon, NI Cho IEEE Access 6, 63094-63106, 2018 | 29 | 2018 |
A new convolutional network-in-network structure and its applications in skin detection, semantic segmentation, and artifact reduction Y Kim, I Hwang, NI Cho arXiv preprint arXiv:1701.06190, 2017 | 29 | 2017 |
Noise-Robust Pupil Center Detection Through CNN-Based Segmentation With Shape-Prior Loss SY Han, HJ Kwon, Y Kim, NI Cho IEEE Access 8, 64739-64749, 2020 | 28 | 2020 |
Dual path denoising network for real photographic noise YI Jang, Y Kim, NI Cho IEEE Signal Processing Letters 27, 860-864, 2020 | 14 | 2020 |
Pupil Center Detection Based on the UNet for the User Interaction in VR and AR Environments SY Han, Y Kim, SH Lee, NI Cho 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), 958-959, 2019 | 14 | 2019 |
Block-Matching Convolutional Neural Network (BMCNN): Improving CNN-Based Denoising by Block-Matched Inputs B Ahn, Y Kim, G Park, NI Cho 2018 Asia-Pacific Signal and Information Processing Association Annual …, 2018 | 10 | 2018 |
Towards Unified Scene Text Spotting based on Sequence Generation T Kil, S Kim, S Seo, Y Kim, D Kim Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 9 | 2023 |
Skin detection based on multi-seed propagation in a multi-layer graph for regional and color consistency I Hwang, Y Kim, NI Cho 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 9 | 2017 |
Electronic apparatus and control method thereof H Lee, D Kim, Y Moon, AHN Taegyoung, KIM Yoonsik, J Park, JW Soh, ... US Patent 11,153,575, 2021 | 8 | 2021 |
RewriteNet: Realistic Scene Text Image Generation via Editing Text in Real-world Image J Lee, Y Kim, S Kim, M Yim, S Shin, G Lee, S Park arXiv preprint arXiv:2107.11041, 2021 | 8 | 2021 |
DEER: Detection-agnostic End-to-End Recognizer for Scene Text Spotting S Kim, S Shin, Y Kim, HC Cho, T Kil, J Surh, S Park, B Lee, Y Baek arXiv preprint arXiv:2203.05122, 2022 | 7 | 2022 |