HIGHLIGHTS
- who: Qianru Teng and collaborators from the Shanghai Institute for Advanced Communication and Data Science, Shanghai, China have published the research work: Occlusion-Aware Unsupervised Learning of Monocular Depth, Optical Flow and Camera Pose with Geometric Constraints, in the Journal: Future Internet 2018, 10, 92 of /2018/
- what: The authors propose a jointly learning network in an utterly unsupervised manner to predict depth, camera pose and optical flow from monocular video sequences with no labeling data or ground truth. The authors focus on avoiding these shortcomings and elaborate on them to achieve more accurate results . . .
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