深度学习相关的一些Review / Survey
开题开题要开题！开题push我短时间狂看了超级多文献（心虚地表示过得都很粗，唉、、、毕竟要先解决文献综述），题目涉及多源数据融合，室内场景重建。自己去溯源一个方向的发展和技术变革真的难，尤其是现在知识技术更新这么快，当下新技术层出不穷，初学者甚至入门好几年的人也未必能快速分辨一项工作的价值，这才意识到，综述不是谁不谁都能写的！！梳理前人工作，并且准确把握当下方向，也给后人提供一个快速的参考。瑞思拜！！！感觉必须应该要被更多的人知道和使用！
形式说明：
【基于篇幅限制（都整理出来了自己去看啊~），只放 题目（链接地址）+发表年份+引用+摘要截图】
语义分割（2D image、3D point cloud）
《A Review on Deep Learning Techniques Applied to Semantic Segmentation》2017
作者：A. Garcia-Garcia, S. Orts-Escolano, S.O. Oprea, V. Villena-Martinez, and J. Garcia-Rodriguez
cite： Garcia-Garcia A , Orts-Escolano S , Oprea S , et al. A Review on Deep Learning Techniques Applied to Semantic Segmentation[J]. 2017.
《A Review of Deep Learning-Based Semantic Segmentation for Point Cloud》2019
作者：JIAYING ZHANG , XIAOLI ZHAO , ZHENG CHEN , AND ZHEJUN LU
cite： Zhang J , Zhao X , Chen Z , et al. A Review of Deep Learning-Based Semantic Segmentation for Point Cloud[J]. IEEE Access, 2019, 7:179118-179133.
三维重建（single image、RGB-D、SLAM）
《Single image 3D object reconstruction based on deep learning：A review》2020
作者：Kui Fu1 & Jiansheng Peng1,2 & Qiwen He1 & Hanxiao Zhang2
cite： Fu K , Peng J , He Q , et al. Single image 3D object reconstruction based on deep learning: A review[J]. Multimedia Tools and Applications, 2020:1-36.
《State of the Art on 3D Reconstruction with RGB-D Cameras》2018
作者：Michael Zollhöfer1;2, Patrick Stotko3, Andreas Görlitz4, Christian Theobalt1, Matthias Nießner5, Reinhard Klein3, Andreas Kolb4
cite：Zollhöfer, Michael, Stotko P , Görlitz, Andreas, et al. State of the Art on 3D Reconstruction with RGB-D Cameras[J]. Computer Graphics Forum, 2018, 37(2):625-652.
《Visual SLAM algorithms-a survey from 2010 to 2016》2017
作者：Takafumi Taketomi1*, Hideaki Uchiyama2 and Sei Ikeda3
cite： Taketomi T , Uchiyama H , Ikeda S . Visual SLAM algorithms: a survey from 2010 to 2016[J]. Ipsj Transactions on Computer Vision & Applications, 2017, 9(1):16.
室内场景理解（2.5D-3D）
《Indoor Scene Understanding in 2.5_3D for Autonomous Agents： A Survey》2019
作者：MUZAMMAL NASEER 1, SALMAN KHAN2,3, AND FATIH PORIKLI 1,
cite： Naseer M , Khan S , Porikli F . Indoor Scene Understanding in 2.5/3D for Autonomous Agents: A Survey[J]. IEEE Access, 2019, 7:1859-1887.
自动驾驶（点云数据、融合数据）
《Deep Learning for LiDAR Point Clouds in Autonomous Driving：A Review》2020
作者：Ying Li ,Zilong Zhong , Dongpu Cao,
cite： Li Y , Ma L , Zhong Z , et al. Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review[J]. IEEE Transactions on Neural Networks and Learning Systems, 2020, PP(99):1-21.
《Deep Learning for Image and Point Cloud Fusion in Autonomous Driving： A Review 》2020
作者：Yaodong Cui, Ren Chen, Wenbo Chu, Long Chen, Daxin Tian, Ying Li, Dongpu Cao
cite： Cui Y , Chen R , Chu W , et al. Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review[J]. 2020.
点云数据（分类、检测、分割）
《Deep Learning for 3D Point Clouds：A Survey》2020
作者：Yulan Guo, Hanyun Wang, Qingyong Hu, Hao Liu, Li Liu, and Mohammed Bennamoun
cite：Guo Y , Wang H , Hu Q , et al. Deep Learning for 3D Point Clouds: A Survey[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, PP(99):1-1.