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[1]梁 煜,张金铭,张 为. 一种改进的卷积神经网络的室内深度估计方法[J].天津大学学报(自然科学与工程技术版),2020,53(08):840-846.[doi:10.11784/tdxbz201906008]
 Liang Yu,Zhang Jinming,Zhang Wei. An Improved Indoor Depth Estimation Method Using Convolutional Neural Networks[J].Journal of Tianjin University(Science and Technology),2020,53(08):840-846.[doi:10.11784/tdxbz201906008]
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 一种改进的卷积神经网络的室内深度估计方法

参考文献/References:

 

[1] Laina IRupprecht CBelagiannis Vet al. Deeper depth prediction with fully convolutional residual networks[C]// 2016 4th International Conference on 3D Vision. StanfordCAUSA2016239-248.

[2] Dharmasiri TSpek ADrummond T. Joint prediction of depthsnormals and surface curvature from RGB images using CNNs[C]// 2017 IEEE International Conference on Intelligent Robots and Systems. VancouverBCCanada20171505-1512.

[3] Fu HGong MWang C Het al. Deep ordinal regression network for monocular depth estimation[C]// 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Salt Lake CityUTUSA20182002-2011.

[4] Shelhamer ELong JDarrell T. Fully convolutional networks for semantic segmentation[J]. IEEE Transac-tions on Pattern Analysis and Machine Intelligence2017(39)640-651.

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[7] Owen A B. A robust hybrid of lasso and ridge regression[J]. Contemporary Mathematics2007(443)59-71.

[8] Silberman NHoiem DKohli Pet al. Indoor segmentation and support inference from RGBD images[C]// 2012 IEEE European Conference on Computer Vision. FlorenceItaly2012746-760.

[9] Eigen DPuhrsch CFergus R. Depth map prediction from a single image using a multi-scale deep network [C]// 2014 Conference and Workshop on Neural Information Processing Systems. MontrealCanada20142366-2374.

[10] Hu JOzay MZhang Yet al. Revisiting single image depth estimationToward higher resolution maps with accurate object boundaries[C]// 2019 IEEE Winter Conference on Applications of Computer Vision. Waikoloa VillageHIUSA20191043-1051.

[11] Liu FShen CLin G. Deep convolutional neural fields for depth estimation from a single image[C]//2015 IEEE Conference on Computer Vision and Pattern Recognition. BostonMAUSA20155162-5170.

[12] Xu DRicci EOuyang Wet al. Multi-scale continuous crfs as sequential deep networks for monocular depth estimation[C]// 2017 IEEE Conference on Computer Vision and Pattern Recognition. HonoluluHIUSA2017161-169.

[13] Zhang ZXu CYang JGao Jet al. Progressive hard-mining network for monocular depth estimation [J]IEEE Transactions on Image Processing201827(8)3691-3702. Liu JWang YLi Yet al. Collaborative deconvolutional neural networks for joint depth estimation and semantic segmentation[J]. IEEE Transactions on Neural Networks and Learning Systems201829(11)5655-5666.

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备注/Memo

 通信作者:张 为,tjuzhangwei@tju.edu.cn

更新日期/Last Update: 2020-07-15