Skip to main content
SpringerLink
Log in

Indoor layout programming via virtual navigation detectors

  • 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. He K M, Zhang X Y, Ren S Q, et al. Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016. 770–778

  2. Song S R, Yu F, Zeng A, et al. Semantic scene completion from a single depth image. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2017. 190–198

  3. Zhu Y K, Mottaghi R, Kolve E, et al. Target-driven visual navigation in indoor scenes using deep reinforcement learning. In: Proceedings of 2017 IEEE International Conference on Robotics and Automation (ICRA), 2017. 3357–3364

  4. Fu Q, Chen X W, Wang X T, et al. Adaptive synthesis of indoor scenes via activity-associated object relation graphs. ACM Trans Graph, 2017, 36: 1–13

    Google Scholar 

  5. Wang K, Savva M, Chang A X, et al. Deep convolutional priors for indoor scene synthesis. ACM Trans Graph, 2018, 37: 1–14

    Google Scholar 

Download references

Acknowledgements

This work was partially supported by National Natural Science Foundation of China (Grant No. 61902032), NSF (Grant No. IIS-1524782), City University of Hong Kong (Grant No. 7004915), Fundamental Research Funds for the Central Universities, the Open Project Program of the State Key Laboratory of Virtual Reality Technology and Systems, Beihang University (Grant Nos. VRLAB2018C11, VRLAB2019B01), and Shenzhen Research Institute, City University of Hong Kong.

Author information

Authors and Affiliations

  1. School of Digital Media and Design Arts, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Qiang Fu & Xueming Li

  2. School of Creative Media, City University of Hong Kong, Hong Kong, 999077, China

    Hongbo Fu

  3. Department of Computer Science, University of Houston, Houston, TX, 77204, USA

    Zhigang Deng

Authors
  1. Qiang Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hongbo Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhigang Deng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xueming Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xueming Li.

Supplementary File

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fu, Q., Fu, H., Deng, Z. et al. Indoor layout programming via virtual navigation detectors. Sci. China Inf. Sci. 65, 189101 (2022). https://doi.org/10.1007/s11432-019-2930-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11432-019-2930-x

Search

Navigation