Relative Depth Order Estimation Using Multi-Scale Densely Connected Convolutional Networks
We study the problem of estimating the relative depth order of point pairs in a monocular image. Recent advances mainly focus on using deep convolutional neural networks to learn and infer the ordinal information from multiple contextual information of the point pairs, such as global scene context,...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8661614/ |