• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Scopus
  4. Deep video coding with gradient-descent optimized motion compensation and Lanczos filtering
 
  • Details
  • Full
Options
2022
Conference Paper
Title

Deep video coding with gradient-descent optimized motion compensation and Lanczos filtering

Abstract
Variational autoencoders have shown promising results for still image compression and have gained a lot of consideration in this field. Recently, noteworthy attempts were made to extend such end-to-end methods to the setting of video compression. Here, low-latency scenarios have been commonly investigated. In this paper, it is shown that the compression efficiency in this setting is improved by applying tools that are typically used in block-based hybrid coding such as rate-distortion optimized encoding of the features and advanced interpolation filters for computing samples at fractional positions. Additionally, a separate motion estimation network is trained to further increase the compression efficiency. Experimental results show that the rate-distortion performance benefits from including the aforementioned tools.
Author(s)
Pientka, Sophie
Fraunhofer-Institut für Nachrichtentechnik, Heinrich-Hertz-Institut HHI  
Schäfer, Michael
Fraunhofer-Institut für Nachrichtentechnik, Heinrich-Hertz-Institut HHI  
Pfaff, Jonathan
Fraunhofer-Institut für Nachrichtentechnik, Heinrich-Hertz-Institut HHI  
Schwarz, Heiko  
Fraunhofer-Institut für Nachrichtentechnik, Heinrich-Hertz-Institut HHI  
Marpe, Detlev  
Fraunhofer-Institut für Nachrichtentechnik, Heinrich-Hertz-Institut HHI  
Wiegand, Thomas  
Fraunhofer-Institut für Nachrichtentechnik, Heinrich-Hertz-Institut HHI  
Mainwork
Picture Coding Symposium, PCS 2022. Proceedings  
Conference
Picture Coding Symposium 2022  
DOI
10.1109/PCS56426.2022.10018006
Language
English
Fraunhofer-Institut für Nachrichtentechnik, Heinrich-Hertz-Institut HHI  
Keyword(s)
  • deep learning

  • motion compensation

  • Rate-Distortion Optimization

  • Variational autoencoders

  • video compression

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024