[4] WANG H H, RAJ B. A survey: time travel in deep learning space: an introduction to deep learning models and how deep learning models evolved from the initial ideas[J]. Computer Science, 226, 23-34(2015).

[5] [5] EIGEN D, PUHRSCH C, FERGUS R. Depth map prediction from a single image using a multiscale deep wk[C]Proceedings of the 27th international conference on neural infmation processing systems. Montreal, Canada: MIT Press, 2014.

[6] SHELHAMER E, LONG J, DARRELL T. Fully convolutional networks for semantic segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 640-651(2017).

[7] [7] LAINA I, RUPPRECHT C, BELAGIANNIS V, et al. Deeper depth prediction with fully convolutional residual wks[C]Proceedings of the 4th international conference on 3D vision (3DV). Stanfd: IEEE, 2016.

[8] [8] HE K M, ZHANG X Y, REN S Q, et al. Deep residual learning f image recognition[C]Proceedings of 2016 IEEE conference on computer vision pattern recognition. Las Vegas: IEEE, 2016.

[9] [9] GARG R, VIJAY KUMAR B G, CARNEIRO G, et al. Unsupervised CNN f single view depth estimation: geometry to the rescue[C]Proceedings of the 14th European conference. Cham: Springer, 2016: 740756.

[10] WANG Z, BOVIK A C, SHEIKH H R. Image quality assessment: from error visibility to structural similarity[J]. IEEE Transactions on Image Processing, 13, 600-612(2004).

[11] PAN S J, YANG Q. A survey on transfer learning[J]. IEEE Transactions on Knowledge and Data Engineering, 22, 1345-1359(2010).

[12] GEIGER A, LENZ P, STILLER C. Vision meets robotics: the KITTI dataset[J]. International Journal of Robotics Research, 32, 1231-1237(2013).

[13] KINGMA D P, BA J. Adam: a method for stochastic optimization[J]. Computer Science(2014).

[14] SAXENA A, SUN M, Ng A Y. Make3D: learning 3D scene structure from a single still image[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31, 824-840(2009).