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Indoor layout programming via virtual navigation detectors

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References

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  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

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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.

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Correspondence to Xueming Li.

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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

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

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