T1.1
DEVICE INTEROPERABILITY FOR LEARNED IMAGE COMPRESSION WITH WEIGHTS AND ACTIVATIONS QUANTIZATION
Esin Koyuncu, Friedrich-Alexander-Universität Erlangen-Nürnberg and Huawei Technologies, Germany; Timofey Solovyev, Elena Alshina, Huawei Technologies, Germany; André Kaup, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
Session:
Towards Practical Learning-based Image and Video Coding
Track:
Special Sessions
Location:
Almaden Ballroom
Presentation Time:
Thu, 8 Dec, 10:30 - 10:48 PST (UTC -7)
Session Co-Chairs:
Wen-Hsiao Peng, National Chiao Tung University and Heming Sun, Waseda University
Presentation
Discussion
Resources
No resources available.
Session T1
T1.1: DEVICE INTEROPERABILITY FOR LEARNED IMAGE COMPRESSION WITH WEIGHTS AND ACTIVATIONS QUANTIZATION
Esin Koyuncu, Friedrich-Alexander-Universität Erlangen-Nürnberg and Huawei Technologies, Germany; Timofey Solovyev, Elena Alshina, Huawei Technologies, Germany; André Kaup, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
T1.2: BLOCK-LEVEL RATE CONTROL FOR LEARNT IMAGE COMPRESSION
Xining Wang, Ming Lu, Zhan Ma, Nanjing University, China
T1.3: CONTENT-ADAPTIVE MOTION RATE ADAPTION FOR LEARNED VIDEO COMPRESSION
Chih-Hsuan Lin, Yi-Hsin Chen, Wen-Hsiao Peng, National Yang Ming Chiao Tung University, Taiwan
T1.4: DEEP VIDEO CODING WITH GRADIENT-DESCENT OPTIMIZED MOTION COMPENSATION AND LANCZOS FILTERING
Sophie Pientka, Michael Schäfer, Jonathan Pfaff, Heiko Schwarz, Detlev Marpe, Thomas Wiegand, Fraunhofer HHI, Germany
T1.5: Sandwiched Image Compression: Increasing the resolution and dynamic range of standard codecs
Onur Guleryuz, Philip Chou, Hugues Hoppe, Danhang Tang, Ruofei Du, Philip Davidson, Sean Fanello, Google Research, United States of America