WA2.L3.5
IMAGE CODING FOR MACHINE VIA ANALYTICS-DRIVEN APPEARANCE REDUNDANCY REDUCTION
Xuelin Shen, Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), China; Haoqiao Ou, Shenzhen University, China; Wenhan Yang, Peng Cheng Laboratory, China
Session:
WA2.L3: Image and Video Coding for Machines Lecture
Track:
Image and Video Communications
Location:
Lecture Room 3
Presentation Time:
Wed, 30 Oct, 11:42 - 12:00 Gulf Standard Time (UTC +4)
Session Chair:
Zhibo Chen, Univeristu of Science and Technology of China
Session WA2.L3
WA2.L3.1: ON ANNOTATION-FREE OPTIMIZATION OF VIDEO CODING FOR MACHINES
Marc Windsheimer, Fabian Brand, André Kaup, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
WA2.L3.2: MFLFC:MULTI-FRAME FUSION BASED LOW-RESOLUTION FEATURE COMPRESSION FOR OBJECT TRACKING
Yi Peng, Zixiang Zhang, Li Yu, Huazhong University of Science and Technology, China
WA2.L3.3: HYBRID SINGLE INPUT AND MULTIPLE OUTPUT METHOD FOR COMPRESSING FEATURES TOWARDS MACHINE VISION TASKS
Zifu Zhang, Shengxi Li, Tie Liu, Mai Xu, Tao Xu, Zhenyu Guan, Beihang University, China; Zhuoyi Lv, VIVO, China
WA2.L3.4: COMPETITIVE LEARNING FOR ACHIEVING CONTENT-SPECIFIC FILTERS IN VIDEO CODING FOR MACHINES
Honglei Zhang, Jukka Ahonen, Nam Le, Ruiying Yang, Francesco Cricri, Nokia Technologies, Finland
WA2.L3.5: IMAGE CODING FOR MACHINE VIA ANALYTICS-DRIVEN APPEARANCE REDUNDANCY REDUCTION
Xuelin Shen, Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), China; Haoqiao Ou, Shenzhen University, China; Wenhan Yang, Peng Cheng Laboratory, China
Contacts