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RGB-D Object Recognition Using Deep Convolutional Neural Networks
2017
2017 IEEE International Conference on Computer Vision Workshops (ICCVW)
We address the problem of object recognition from RGB-D images using deep convolutional neural networks (CNNs). We advocate the use of 3D CNNs to fully exploit the 3D spatial information in depth images as well as the use of pretrained 2D CNNs to learn features from RGB-D images. There exists currently no large scale dataset available comprising depth information as compared to those for RGB data. Hence transfer learning from 2D source data is key to be able to train deep 3D CNNs. To this end,
doi:10.1109/iccvw.2017.109
dblp:conf/iccvw/ZiaYYY17
fatcat:atpqmvnuo5d2bciwxjmy5kp7jm