no code implementations • 6 Apr 2024 • Gwanghyun Kim, Hayeon Kim, Hoigi Seo, Dong Un Kang, Se Young Chun
We propose BeyondScene, a novel framework that overcomes prior limitations, generating exquisite higher-resolution (over 8K) human-centric scenes with exceptional text-image correspondence and naturalness using existing pretrained diffusion models.
no code implementations • 30 Nov 2023 • Gwanghyun Kim, Dong Un Kang, Hoigi Seo, Hayeon Kim, Se Young Chun
Text-driven large scene image synthesis has made significant progress with diffusion models, but controlling it is challenging.
1 code implementation • ICCV 2023 • Hwihun Jeong, Heejoon Byun, Dong Un Kang, Jongho Lee
These differences in images create a domain gap that needs to be bridged by a step called image harmonization, to process the images successfully using conventional or deep learning-based image analysis (e. g., segmentation).
no code implementations • 4 Jul 2022 • Okchul Jung, Dong Un Kang, Gwanghyun Kim, Se Young Chun
The experimental results show that the proposed method improve the detection performance with large margin without much difficult modification to the model.
no code implementations • 23 Dec 2020 • Dongwon Park, Dong Un Kang, Se Young Chun
Secondly, we propose multi-blurring recurrent neural network (MBRNN) that can synthesize more blurred images from neighboring frames, yielding substantially improved performance with existing video deblurring methods.
Ranked #5 on Deblurring on DVD (using extra training data)
1 code implementation • ECCV 2020 • Dongwon Park, Dong Un Kang, Jisoo Kim, Se Young Chun
Multi-scale (MS) approaches have been widely investigated for blind single image / video deblurring that sequentially recovers deblurred images in low spatial scale first and then in high spatial scale later with the output of lower scales.
Ranked #14 on Deblurring on HIDE (trained on GOPRO)