Unsupervised Monocular Depth Estimation by Fusing Dilated Convolutional Network and SLAM

Renyue Dai; Zhijun Fang; Yongbin Gao

doi:10.3788/LOP57.061007

[1] Pan X L, You Y R, Wang Z Y et al. Virtual to real reinforcement learning for autonomous driving[C]∥Proceedings of the British Machine Vision Conference 2017, September 2017, London, UK., 11(2017).

[2] Zeng Z P, Zhang J L, Wei Z S et al. Three-dimensional reconstruction method based on smartphone imaging[J]. Laser & Optoelectronics Progress, 55, 111502(2018).

[3] Michalos G, Karagiannis P, Makris S et al. Augmented reality (AR) applications for supporting human-robot interactive cooperation[J]. Procedia CIRP, 41, 370-375(2016).

[4] Zhou T H, Brown M, Snavely N et al. Unsupervised learning of depth and ego-motion from video. [C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 6612-6621(2017).

[5] Eigen D, Puhrsch C, Fergus R. Depth map prediction from a single image using a multi-scale deep network. [C]∥Advances in Neural Information Processing Systems, December 8-13, 2014, Montreal, Quebec, Canada. Canada: NIPS, 2366-2374(2014).

[6] Eigen D, Fergus R. Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture. [C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 2650-2658(2015).

[7] Liu F Y, Shen C H, Lin G S. Deep convolutional neural fields for depth estimation from a single image. [C]∥2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE, 5162-5170(2015).

[8] Wang A J, Fang Z J, Gao Y B et al. Depth estimation of video sequences with perceptual losses[J]. IEEE Access, 6, 30536-30546(2018).

[9] Tosi F, Aleotti F, Poggi M et al. Learning monocular depth estimation infusing traditional stereo knowledge. [C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition(CVPR), June 16-20, 2019, Long Beach, CA. New York: IEEE, 9799-9809(2019).

[10] Li Y, Chen X W, Wang Y et al. Progress in deep learning based monocular image depth estimation[J]. Laser & Optoelectronics Progress, 56, 190001(2019).

[11] Garg R. Vijay K B G, Carneiro G, et al. Unsupervised CNN for single view depth estimation: geometry to the rescue[M]. ∥Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science. Cham: Springer, 9912, 740-756(2016).

[12] Mayer N, Ilg E, Hausser P et al. A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 4040-4048(2016).

[13] Zhan H Y, Garg R, Weerasekera C S et al. Unsupervised learning of monocular depth estimation and visual odometry with deep feature reconstruction. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 340-349(2018).

[14] Li S M, Lei G Q, Fan R. Depth map super-resolution reconstruction based on convolutional neural networks[J]. Acta Optica Sinica, 37, 1210002(2017).

[15] Zhou X Y, Zheng J Q. -01-26)[2019-07-03]. https:∥arxiv.gg363., site/abs/1901, 09203(2019).

[16] Chen S, Wang L. An improved SIFT feature matching based on RANSAC algorithm[J]. Information Technology, 40, 39-43(2016).

[17] Shi G J, Xu X Y, Dai Y P. SIFT feature point matching based on improved RANSAC algorithm. [C]∥2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, August 26-27, 2013, Hangzhou, China. New York: IEEE, 474-477(2013).

[18] Chen J W, Quan S B, Quan Y M et al. Calibration method of relative position and pose between dual two-dimensional laser radar[J]. Chinese Journal of Lasers, 44, 1004005(2017).

[19] Kingma D P. -01-30)[2019-07-03]. https:∥arxiv., org/abs/1412, 6980(2017).

[20] Luo C X, Yang Z H, Wang P et al. Every pixel counts ++: joint learning of geometry and motion with 3D holistic understanding[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1(2019).

[21] Li R H, Wang S, Long Z Q et al. UnDeepVO: monocular visual odometry through unsupervised deep learning. [C]∥2018 IEEE International Conference on Robotics and Automation (ICRA), May 21-25, 2018, Brisbane, QLD, Australia. New York: IEEE, 7286-7291(2018).

[22] Kumar A R S, Bhandarkar S M, Prasad M. Monocular depth prediction using generative adversarial networks. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), June 18-22, 2018, Salt Lake City, UT, USA. New York: IEEE, 413-421(2018).