Yuejin Sun
A5021355446- Image and Signal Denoising Methods
- Image Enhancement Techniques
- Advanced Image Processing Techniques
- Digital Media Forensic Detection
- Advanced Data Compression Techniques
- Image and Video Quality Assessment
- 3D Surveying and Cultural Heritage
- Retinal Imaging and Analysis
University of Science and Technology of China
2022-2024
Seoul National University
2021
Motion blur is a common photography artifact in dynamic environments that typically comes jointly with the other types of degradation. This paper reviews NTIRE 2021 Challenge on Image Deblurring. In this challenge report, we describe specifics and evaluation results from 2 competition tracks proposed solutions. While both aim to recover high-quality clean image blurry image, different artifacts are involved. track 1, images low resolution while compressed JPEG format. each competition, there...
Due to the wide dynamic range in real low-light scenes, there will be large differences degree of contrast degradation and detail blurring captured images, making it difficult for existing end-to-end methods enhance images normal exposure. To address above issue, we decompose image enhancement into a recursive task propose brightness-perceiving-based framework high enhancement. Specifically, our consists two parallel sub-networks: Adaptive Contrast Texture network (ACT-Net) Brightness...
JPEG is a widely used compression scheme to efficiently reduce the volume of transmitted images. The artifacts appear among blocks due information loss, which not only affects quality images but also harms subsequent high-level tasks in terms feature drifting. High-level vision models trained on high-quality will suffer performance degradation when dealing with compressed images, especially mobile devices. Numerous learning-based artifact removal methods have been proposed handle visual...
JPEG is a widely used compression scheme to efficiently reduce the volume of transmitted images at expense visual perception drop. The artifacts appear among blocks due information loss in process, which not only affects quality but also harms subsequent high-level tasks terms feature drifting. High-level vision models trained on high-quality will suffer performance degradation when dealing with compressed images, especially mobile devices. In recent years, numerous learning-based removal...