T3.5
TENSOR NETWORK-BASED ENTROPY CODING FOR LEARNED IMAGE COMPRESSION
Xiaoxuan Fan, Wen Fei, Wenrui Dai, Chenglin Li, Junni Zou, Hongkai Xiong, Shanghai Jiao Tong University, China
Session:
Learning-Based Compression
Track:
Machine learning for image/video compression
Location:
Almaden Ballroom
Presentation Time:
Thu, 8 Dec, 17:42 - 18:00 PST (UTC -7)
Session Chair:
Ying Liu, Santa Clara University, USA
Presentation
Discussion
Resources
No resources available.
Session T3
T3.1: EFFECTIVE VVC INTRA PREDICTION BASED ON ENSEMBLE LEARNING
Hongji Zeng, Yuhang Huang, Tiesong Zhao, Ludi Wu, fuzhou university, China; Weize Feng, Guowei Cai, fzu.edu.cn, China
T3.2: PERCEPTUAL VIDEO CODING BASED ON SEMANTIC-GUIDED TEXTURE DETECTION AND SYNTHESIS
Chen Zhu, Guo Lu, Rong Xie, Li Song, Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, China
T3.3: LIGHT FIELD COMPRESSION BASED ON IMPLICIT NEURAL REPRESENTATION
Henan Wang, Hanxin Zhu, Zhibo Chen, University of Science and Technology of China, China
T3.4: END-TO-END QUALITY CONTROLLABLE IMAGE COMPRESSION
Luge Wang, Xionghui Mao, Saiping Zhang, Fuzheng Yang, Xidian University, China
T3.5: TENSOR NETWORK-BASED ENTROPY CODING FOR LEARNED IMAGE COMPRESSION
Xiaoxuan Fan, Wen Fei, Wenrui Dai, Chenglin Li, Junni Zou, Hongkai Xiong, Shanghai Jiao Tong University, China