Technical Program

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COM-2: Learning-based Image and Video Coding

Interactive Q&A Time: Wednesday, September 22, 14:30 - 16:00
Session Chair: Simone Milani, University of Padova
 
 COM-2.1: ANALYSIS OF NEURAL IMAGE COMPRESSION NETWORKS FOR MACHINE-TO-MACHINE COMMUNICATION
         Kristian Fischer; Friedrich-Alexander University Erlangen-Nürnberg (FAU)
         Christian Forsch; Friedrich-Alexander University Erlangen-Nürnberg (FAU)
         Christian Herglotz; Friedrich-Alexander University Erlangen-Nürnberg (FAU)
         André Kaup; Friedrich-Alexander University Erlangen-Nürnberg (FAU)
 
 COM-2.2: AN EFFICIENT IMAGE COMPRESSION METHOD BASED ON NEURAL NETWORK: AN OVERFITTING APPROACH
         Yu Mikami; Nagoya University
         Chihiro Tsutake; Nagoya University
         Keita Takahashi; Nagoya University
         Toshiaki Fujii; Nagoya University
 
 COM-2.3: COMPREHENSIVE COMPARISONS OF UNIFORM QUANTIZERS FOR DEEP IMAGE COMPRESSION
         Koki Tsubota; University of Tokyo
         Kiyoharu Aizawa; University of Tokyo
 
 COM-2.4: GRAPH-CONVOLUTION NETWORK FOR IMAGE COMPRESSION
         Chunhui Yang; Shenzhen Graduate School of Peking University
         Yi Ma; Shenzhen Graduate School of Peking University
         Jiayu Yang; Shenzhen Graduate School of Peking University
         Shiyi Liu; Shenzhen Graduate School of Peking University
         Ronggang Wang; Shenzhen Graduate School of Peking University
 
 COM-2.5: LEARNED IMAGE COMPRESSION WITH CHANNEL-WISE GROUPED CONTEXT MODELING
         Liang Yuan; Shanghai Jiao Tong University
         Jixiang Luo; Shanghai Jiao Tong University
         Shaohui Li; Shanghai Jiao Tong University
         Wenrui Dai; Shanghai Jiao Tong University
         Chenglin Li; Shanghai Jiao Tong University
         Junni Zou; Shanghai Jiao Tong University
         Hongkai Xiong; Shanghai Jiao Tong University
 
 COM-2.6: CONVOLUTIONAL NEURAL NETWORK BASED IN-LOOP FILTER FOR VVC INTRA CODING
         Yue Li; Bytedance Inc.
         Li Zhang; Bytedance Inc.
         Kai Zhang; Bytedance Inc.
 
 COM-2.7: CNN-BASED PARAMETER SELECTION FOR FAST VVC INTRA-PICTURE ENCODING
         Gerhard Tech; Fraunhofer Heinrich Hertz Institute
         Jonathan Pfaff; Fraunhofer Heinrich Hertz Institute
         Heiko Schwarz; Fraunhofer Heinrich Hertz Institute
         Philipp Helle; Fraunhofer Heinrich Hertz Institute
         Adam Wieckowski; Fraunhofer Heinrich Hertz Institute
         Detlev Marpe; Fraunhofer Heinrich Hertz Institute
         Thomas Wiegand; Fraunhofer Heinrich Hertz Institute
 
COM-2.8: FAST MULTI-TYPE TREE PARTITIONING FOR VERSATILE VIDEO CODING USING A LIGHTWEIGHT NEURAL NETWORK
         Sang-hyo Park; Kyungpook National University
         Je-Won Kang; Ewha Womans University
 
 COM-2.9: NEURAL NETWORK-BASED ERROR CONCEALMENT FOR VVC
         Martin Benjak; Gottfried Wilhelm Leibniz Universität Hannover
         Yasser Samayoa; Gottfried Wilhelm Leibniz Universität Hannover
         Jörn Ostermann; Gottfried Wilhelm Leibniz Universität Hannover
 
 COM-2.10: INTRA TO INTER: TOWARDS INTRA PREDICTION FOR LEARNING-BASED VIDEO CODERS USING OPTICAL FLOW
         Fabian Brand; Friedrich-Alexander University Erlangen-Nürnberg (FAU)
         Jürgen Seiler; Friedrich-Alexander University Erlangen-Nürnberg (FAU)
         André Kaup; Friedrich-Alexander University Erlangen-Nürnberg (FAU)
 
 COM-2.11: DEEP VIDEO COMPRESSION FOR INTERFRAME CODING
         David Alexandre; National Chiao Tung University
         Hsueh-Ming Hang; National Chiao Tung University
         Wen-Hsiao Peng; National Chiao Tung University
         Marek Domański; Poznań University of Technology