Skip to main content
SpringerLink
Log in

3DPF-FBN: video inpainting by jointly 3D-patch filling and neural network refinement

  • Letter
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  1. Koloda J, Seiler J, Peinado A M, et al. Scalable kernel-based minimum mean square error estimator for accelerated image error concealment. IEEE Trans Broadcast, 2017, 63: 59–70

    Article  Google Scholar 

  2. Granados M, Tompkin J, Kim K, et al. How not to be seen — object removal from videos of crowded scenes. Comput Graph Forum, 2012, 31: 219–228

    Article  Google Scholar 

  3. Liu G, Reda F A, Shih K J, et al. Image inpainting for irregular holes using partial convolutions. In: Proceedings of the European Conference on Computer Vision, Munich, 2018. 85–100

  4. Le T T, Almansa A, Gousseau Y, et al. Motion-consistent video inpainting. In: Proceedings of the IEEE International Conference on Image Processing, Beijing, 2017. 2094–2098

  5. Ilg E, Mayer N, Saikia T, et al. Flownet 2.0: evolution of optical flow estimation with deep networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, 2017. 2462–2470

  6. Ding Y, Wang C, Huang H, et al. Frame-recurrent video inpainting by robust optical flow inference. 2019. ArXiv: 1905.02882

Download references

Acknowledgements

This work was supported by National Key R&D Program of China (Grant No. 2018YFB1801702) and Joint Fund of the Ministry of Education (Grant No. 6141A02033347).

Author information

Authors and Affiliations

  1. State Key Laboratory of Advanced Optical Communication Systems and Networks, Department of Electronics, Peking University, Beijing, 100871, China

    Yan Huang, Chuanchuan Yang & Zhangyuan Chen

Authors
  1. Yan Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chuanchuan Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhangyuan Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chuanchuan Yang.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Huang, Y., Yang, C. & Chen, Z. 3DPF-FBN: video inpainting by jointly 3D-patch filling and neural network refinement. Sci. China Inf. Sci. 65, 179103 (2022). https://doi.org/10.1007/s11432-019-2956-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11432-019-2956-6

Search

Navigation