Learning for Video Compression

@article{Chen2020LearningFV,
  title={Learning for Video Compression},
  author={Zhibo Chen and Tianyu He and X. Jin and Feng Wu},
  journal={IEEE Transactions on Circuits and Systems for Video Technology},
  year={2020},
  volume={30},
  pages={566-576}
}
  • Zhibo Chen, Tianyu He, +1 author Feng Wu
  • Published 2020
  • Computer Science, Engineering
  • IEEE Transactions on Circuits and Systems for Video Technology
One key challenge to learning-based video compression is that motion predictive coding, a very effective tool for video compression, can hardly be trained into a neural network. In this paper, we propose the concept of PixelMotionCNN (PMCNN) which includes motion extension and hybrid prediction networks. PMCNN can model spatiotemporal coherence to effectively perform predictive coding inside the learning network. On the basis of PMCNN, we further explore a learning-based framework for video… Expand
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