Moving SLAM: fully unsupervised deep learning in non-rigid scenes
We propose a new deep learning framework to decompose monocular videos into 3D geometry (camera pose and depth), moving objects, and their motions, with no supervision. We build upon the idea of view synthesis, which uses classical camera geometry to re-render a source image from a different point-o...
Main Authors: | Xu, D, Vedaldi, A, Henriques, JF |
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Format: | Conference item |
Language: | English |
Published: |
IEEE
2021
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