All times are in Alaska local time (AKDT/UTC−08:00)
MLR-APPL-IP-1: Machine learning for image processing 1 |
Interactive Q&A Time: Monday, September 20, 13:30 - 15:00 |
Session Chair: Shan Du, |
MLR-APPL-IP-1.1: MULTI-SCALE FEATURE GUIDED LOW-LIGHT IMAGE ENHANCEMENT |
Lanqing Guo; Nanyang Technological University |
Renjie Wan; Nanyang Technological University |
Guan-Ming Su; Dolby Laboratories |
Alex C. Kot; Nanyang Technological University |
Bihan Wen; Nanyang Technological University |
MLR-APPL-IP-1.2: CASCADE ATTENTION BLEND RESIDUAL NETWORK FOR SINGLE IMAGE SUPER-RESOLUTION |
Tianyu Chen; Southwest University |
Guoqiang Xiao; Southwest University |
Xiaoqin Tang; Southwest University |
Xianfeng Han; Southwest University |
Wenzhuo Ma; Chongqing Productivity Council |
Xinye Gou; Chongqing Productivity Council |
MLR-APPL-IP-1.3: SCALE-INVARIANT SALIENT EDGE DETECTION |
Gang Hu; State University of New York @ Buffalo State |
Conner Saeli; State University of New York @ Buffalo State |
MLR-APPL-IP-1.4: TWO-STAGE DOMAIN ADAPTED TRAINING FOR BETTER GENERALIZATION IN REAL-WORLD IMAGE RESTORATION AND SUPER-RESOLUTION |
Cansu Korkmaz; Koç University |
Ahmet Murat Tekalp; Koç University |
Zafer Dogan; Koç University |
MLR-APPL-IP-1.5: LEARNING TO DISENTANGLE REPRESENTATIONS FOR RAIN STREAK REMOVAL |
Younkwan Lee; Gwangju Institute of Science and Technology |
Hyeongjun Yoo; Gwangju Institute of Science and Technology |
Moongu Jeon; Gwangju Institute of Science and Technology |
MLR-APPL-IP-1.6: QUALITY ASSESSMENT OF SCREEN CONTENT IMAGES BASED ON CONVOLUTIONAL NEURAL NETWORK WITH DUAL PATHWAYS |
Yongli Chang; Tianjin University |
Sumei Li; Tianjin University |
Anqi Liu; Tianjin University |
MLR-APPL-IP-1.7: IMPROVING THE QUALITY OF ILLUSTRATIONS: TRANSFORMING AMATEUR ILLUSTRATIONS TO A PROFESSIONAL STANDARD |
Keita Awane; University of Tokyo |
Koki Tsubota; University of Tokyo |
Hikaru Ikuta; University of Tokyo |
Yusuke Matsui; University of Tokyo |
Kiyoharu Aizawa; University of Tokyo |
Naohiro Yanase; BOOK WALKER Co.,Ltd. |
MLR-APPL-IP-1.8: SELF-ORGANIZED RESIDUAL BLOCKS FOR IMAGE SUPER-RESOLUTION |
Onur Keles; Koç University |
Ahmet Murat Tekalp; Koç University |
Junaid Malik; Tampere University |
Serkan Kiranyaz; Qatar University |
MLR-APPL-IP-1.9: A UNIFIED DENSITY-DRIVEN FRAMEWORK FOR EFFECTIVE DATA DENOISING AND ROBUST ABSTENTION |
Krishanu Sarker; Georgia State University |
Xiulong Yang; Georgia State University |
Yang Li; Georgia State University |
Saeid Belkasim; Georgia State University |
Shihao Ji; Georgia State University |
MLR-APPL-IP-1.10: QUALITY AND COMPLEXITY ASSESSMENT OF LEARNING-BASED IMAGE COMPRESSION SOLUTIONS |
João Dick; Federal University of Rio Grande do Sul |
Brunno Abreu; Federal University of Rio Grande do Sul |
Mateus Grellert; Federal University of Santa Catarina |
Sergio Bampi; Federal University of Rio Grande do Sul |
MLR-APPL-IP-1.11: ACCURATE COMPENSATION MAKES THE WORLD MORE CLEAR FOR THE VISUALLY IMPAIRED |
Sijing Wu; Shanghai Jiao Tong University |
Huiyu Duan; Shanghai Jiao Tong University |
Xiongkuo Min; Shanghai Jiao Tong University |
Danyang Tu; Shanghai Jiao Tong University |
Guangtao Zhai; Shanghai Jiao Tong University |