activity
20222026
most citedMeta Transferring for Deblurring

2 citations · 2 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2026

UniVerse: A Unified Modulation Framework for Segmentation-Free,Disentangled Multi-Concept Personalization

Quynh Phung, Sandesh Ghimire, Minsi Hu +2

Personalized visual understanding has advanced significantly, yet existing approaches struggle to localize and extract specific concepts when input images contain multiple objects.…

cs.CV2024

Domain-adaptive Video Deblurring via Test-time Blurring

Jin-Ting He, Fu-Jen Tsai, Jia-Hao Wu +4

Dynamic scene video deblurring aims to remove undesirable blurry artifacts captured during the exposure process. Although previous video deblurring methods have achieved impressive…

cs.CV2024

Image Deraining via Self-supervised Reinforcement Learning

He-Hao Liao, Yan-Tsung Peng, Wen-Tao Chu +2

The quality of images captured outdoors is often affected by the weather. One factor that interferes with sight is rain, which can obstruct the view of observers and computer visio…

cs.CV2023

ViStripformer: A Token-Efficient Transformer for Versatile Video Restoration

Fu-Jen Tsai, Yan-Tsung Peng, Chen-Yu Chang +4

Video restoration is a low-level vision task that seeks to restore clean, sharp videos from quality-degraded frames. One would use the temporal information from adjacent frames to…

cs.CV2023

ID-Blau: Image Deblurring by Implicit Diffusion-based reBLurring AUgmentation

Jia-Hao Wu, Fu-Jen Tsai, Yan-Tsung Peng +3

Image deblurring aims to remove undesired blurs from an image captured in a dynamic scene. Much research has been dedicated to improving deblurring performance through model archit…

cs.CV20222 cited

Meta Transferring for Deblurring

Po-Sheng Liu, Fu-Jen Tsai, Yan-Tsung Peng +3

Most previous deblurring methods were built with a generic model trained on blurred images and their sharp counterparts. However, these approaches might have sub-optimal deblurring…