7 citations · 17 across the 4 of their papers we have counts for
6 papers
Joint Self-Attention and Scale-Aggregation for Self-Calibrated Deraining Network
Cong Wang, Yutong Wu, Zhixun Su +1
In the field of multimedia, single image deraining is a basic pre-processing work, which can greatly improve the visual effect of subsequent high-level tasks in rainy conditions. I…
DCSFN: Deep Cross-scale Fusion Network for Single Image Rain Removal
Cong Wang, Xiaoying Xing, Zhixun Su +1
Rain removal is an important but challenging computer vision task as rain streaks can severely degrade the visibility of images that may make other visions or multimedia tasks fail…
Physical Model Guided Deep Image Deraining
Honghe Zhu, Cong Wang, Yajie Zhang +2
Single image deraining is an urgent task because the degraded rainy image makes many computer vision systems fail to work, such as video surveillance and autonomous driving. So, de…
Non-rigid 3D shape retrieval based on multi-view metric learning
Haohao Li, Shengfa Wang, Nannan Li +2
This study presents a novel multi-view metric learning algorithm, which aims to improve 3D non-rigid shape retrieval. With the development of non-rigid 3D shape analysis, there exi…
Learning Video-Story Composition via Recurrent Neural Network
Guangyu Zhong, Yi-Hsuan Tsai, Sifei Liu +2
In this paper, we propose a learning-based method to compose a video-story from a group of video clips that describe an activity or experience. We learn the coherence between video…
Deep Blind Image Inpainting
Yang Liu, Jinshan Pan, Zhixun Su
Image inpainting is a challenging problem as it needs to fill the information of the corrupted regions. Most of the existing inpainting algorithms assume that the positions of the…