- 1.
Aldoma A, Tombari F, Di Stefano L and Vincze M. 2012. A global hypotheses verification method for 3D object recognition//Lazebnik A, Fitzgibbon S, Perona P, Sato Y and Schmidt C, eds. Computer Vision - ECCV 2012. Florence, Italy: Springer: 511-524
- 2.
Borji A. 2015. What is a salient object? A dataset and a baseline model for salient object detection. IEEE Transactions on Image Processing, 24(2): 742-756
- 3.
Boykov Y, Veksler O and Zabih R. 2001a. Fast approximate energy minimization via graph cuts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(11): 1222-1239
- 4.
Boykov Y Y and Jolly M P. 2001b. Interactive graph cuts for optimal boundary and region segmentation of objects in N-D images//Proceedings Eighth IEEE International Conference on Computer Vision. Vancouver, BC, Canada: IEEE: 105-112
- 5.
Carvalho L E and von Wangenheim A. 2019. 3D object recognition and classification: a systematic literature review. Pattern Analysis and Applications, 22(4): 1243-1292 DOI: ]
- 6.
Chen H T. 2010. Preattentive co-saliency detection//2010 IEEE International Conference on Image Processing. Hong Kong, China: IEEE: 1117-1120
- 7.
Ch’ng E, Cai S D, Zhang T E and Leow F T. 2019. Crowdsourcing 3D cultural heritage: best practice for mass photogrammetry. Journal of Cultural Heritage Management and Sustainable Development, 9(1): 24-42
- 8.
Cong R M, Lei J J, Fu H Z, Cheng M M, Lin W S and Huang Q M. 2019. Review of visual saliency detection with comprehensive information. IEEE Transactions on Circuits and Systems for Video Technology, 29(10): 2941-2959
- 9.
Fu K R, Gu I Y H, Yun Y X, Gong C and Yang J. 2014. Graph construction for salient object detection in videos//2014 22nd International Conference on Pattern Recognition. Stockholm, Sweden: IEEE: 2371-2376
- 10.
Gong Y P, Zhang F, Jia X Y, Huang X F, Li D R and Mao Z. 2021.“Deep Neural Networks for Quantitative Damage Evaluation ofBuilding Losses Using Aerial Oblique Images: Case Study on theGreat Wall (China).” Remote Sensing 13(7): 19
- 11.
Guo Y L, Bennamoun M, Sohel F, Lu M and Wan J W. 2014. 3D object recognition in cluttered scenes with local surface features: a survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(11): 2270-2287
- 12.
Guo Y L, Wang H Y, Hu Q Y, Liu H, Liu L and Bennamoun M. 2020. Deep learning for 3D point clouds: a survey. IEEE Transactions on Pattern Analysis and Machine Intelligence
- 13.
Han J W, Zhang D W, Cheng G, Liu N and Xu D. 2018. Advanced deep-learning techniques for salient and category-specific object detection: a survey. IEEE Signal Processing Magazine, 35(1): 84-100
- 14.
He K M, Gkioxari G, Dollár P and Girshick R. 2017. Mask R-CNN//2017 IEEE International Conference on Computer Vision. Venice, Italy: IEEE: 2980-2988
- 15.
Jakab M, Benesova W and Racev M. 2015. 3D object recognition based on local descriptors//Proceedings Volume 9406, Intelligent Robots and Computer Vision XXXII: Algorithms and Techniques. San Francisco, California, United States: SPIE: 94060L
- 16.
Li D P, Wang H Y, Liu N, Wang X M and Xu J. 2020. 3D object recognition and pose estimation from point cloud using stably observed point pair feature. IEEE Access, 8: 44335-44345
- 17.
Li H L, Meng F M and Ngan K N. 2013. Co-salient object detection from multiple images. IEEE Transactions on Multimedia, 15(8): 1896-1909
- 18.
Lin T Y, Maire M, Belongie S, Hays J, Perona P, Ramanan D, Dollár P and Zitnick C L. 2014. Microsoft COCO: common objects in context//Fleet D, Pajdla T, Schiele B and Tuytelaars T, eds. Computer Vision - ECCV 2014. Zurich, Switzerland: Springer: 740-555
- 19.
Loaiza C, Daniel A, María M M and Gabriel M B. 2020. “Virtual Museums. Captured Reality and 3d Modeling.” Journal of Cultural Heritage 45: 234-9
- 20.
Luo Y, Yuan J S and Lu J W. 2016. Finding spatio-temporal salient paths for video objects discovery. Journal of Visual Communication and Image Representation, 38: 45-54
- 21.
Peng H W, Li B, Xiong W H, Hu W M and Ji R R. 2014. RGBD salient object detection: a benchmark and algorithms//Fleet D, Pajdla T, Schiele B and Tuytelaars T, eds. Computer Vision - ECCV 2014. Zurich, Switzerland: Springer: 92-109
- 22.
Qu L Q, He S F, Zhang J W, Tian J D, Tang Y D and Yang Q X. 2017. RGBD salient object detection via deep fusion. IEEE Transactions on Image Processing, 26(5): 2274-2285
- 23.
Rother C, Kolmogorov V and Blake A. 2004. “GrabCut”: interactive foreground extraction using iterated graph cuts. ACM Transactions on Graphics, 23(3): 309-314
- 24.
Shen Z Q, Ma X and Li Y B. 2018. A hybrid 3D descriptor with global structural frames and local signatures of histograms. IEEE Access, 6: 39261-39272
- 25.
Singh R D, Mittal A and Bhatia R K. 2019. 3D convolutional neural network for object recognition: a review. Multimedia Tools and Applications, 78(12): 15951-15995
- 26.
Sun X, Yang B S and Li Q Q. 2011. “Structural Segmentation Method for 3d Building Models Based on Voxel Analysis.” Acta Geodeticaet Cartographica Sinica 40 (5):582-6
- 27.
Tang M, Gorelick L, Veksler O and Boykov Y. 2013. GrabCut in one cut//2013 IEEE International Conference on Computer Vision. Sydney, NSW, Australia: IEEE: 1769-1776
- 28.
Ullah I, Jian M W, Hussain S, Guo J, Yu H, Wang X and Yin Y L. 2020. A brief survey of visual saliency detection. Multimedia Tools and Applications, 79(45): 34605-34645
- 29.
Vetrivel A., M. Gerke, N. Kerle, and G. Vosselman. 2015. Segmentation of Uav-Based Images Incorporating 3d Point Cloud Information. Paper presented at the Joint ISPRS Conference on Photogrammetric Image Analysis (PIA) and High Resolution Earth Imaging for Geospatial Information (HRIGI), Technische UnivMunchen, Munich, GERMANY, Mar 25-27
- 30.
Wen W W, Wen G J, Hui B W and Qiu S H. 2018. 3D object recognition based on improved point cloud descriptors//Proceedings Volume 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018. Shanghai, China: SPIE: 108060O
- 31.
Yan Y M, Gao F J, Deng S P, and Su N. 2017. “A Hierarchical Building Segmentation in Digital Surface Models for 3d Reconstruction.”Sensors 17 (2) [DOI: 10.3390/s17020222]
- 32.
Yang C, Zhang F., Gao Y L, Mao Z, Li L, and Huang X F. 2021. “Moving Car Recognition and Removal for 3d Urban Modelling Using Oblique Images.” Remote Sensing 13 (17): 19
- 33.
Zhao Z Q, Zheng P, Xu S T and Wu X D. 2019. Object detection with deep learning: a review. IEEE Transactions on Neural Networks and Learning Systems, 30(11): 3212-3232