MA2.L2.2
SN-NET: SEMISMOOTH NEWTON DRIVEN LIGHTWEIGHT NETWORK FOR REAL-WORLD IMAGE DENOISING
Chenxiao Zhang, Xin Deng, Beihang University, China; Hongpeng Sun, Renmin University of China, China; Jingyi Xu, Mai Xu, Beihang University, China
Session:
MA2.L2: Image and Video Denoising Lecture
Track:
Image and Video Processing
Location:
Lecture Room 2
Presentation Time:
Mon, 28 Oct, 10:48 - 11:06 Gulf Standard Time (UTC +4)
Session Chair:
Yuvraj Parkale, SVPM'S COEM (Bk), SPPU University
Session MA2.L2
MA2.L2.1: WHEN SELF-SUPERVISED PRE-TRAINING MEETS SINGLE IMAGE DENOISING
Hamadi Chihaoui, Paolo Favaro, University of Bern, Switzerland
MA2.L2.2: SN-NET: SEMISMOOTH NEWTON DRIVEN LIGHTWEIGHT NETWORK FOR REAL-WORLD IMAGE DENOISING
Chenxiao Zhang, Xin Deng, Beihang University, China; Hongpeng Sun, Renmin University of China, China; Jingyi Xu, Mai Xu, Beihang University, China
MA2.L2.3: CONSTRUCTING AN INTERPRETABLE DEEP DENOISER BY UNROLLING GRAPH LAPLACIAN REGULARIZER
Seyed Alireza Hosseini, Tam Thuc Do, Gene Cheung, York University, Canada; Yuichi Tanaka, Osaka University, Japan
MA2.L2.4: UNSUPERVISED COORDINATE-BASED VIDEO DENOISING
Mary Aiyetigbo, Dineshchandar Ravichandran, Clemson University, United States of America; Reda Chalhoub, Peter Kalivas, The Medical University of South Carolina, United States of America; Feng Luo, Nianyi Li, Clemson University, United States of America
MA2.L2.5: B-WALK: BERNOULLI PRINCIPLE GUIDED BIASED RANDOM WALK FOR CURVE CONNECTION
Zhuang Sun, Li Chen, Zhida Feng, Xiaoming Liu, School of Computer Science and Technology, China
Contacts