SfM-Net: Learning of Structure and Motion from Video: Difference between revisions
(Created page with "SfM-Net: Learning of Structure and Motion from Video (2017) Authors: Sudheendra Vijayanarasimhan, Susanna Ricco, Cordelia Schmid, Rahul Sukthankar, Katerina Fragkiadaki Affil...") |
(→Method) |
||
| Line 10: | Line 10: | ||
==Method== | ==Method== | ||
==Architecture== | ==Architecture== | ||
==References== | ==References== | ||
Revision as of 19:04, 2 June 2020
SfM-Net: Learning of Structure and Motion from Video (2017)
Authors: Sudheendra Vijayanarasimhan, Susanna Ricco, Cordelia Schmid, Rahul Sukthankar, Katerina Fragkiadaki Affiliations: Google, Inria Research Institute, CMU
SfM-Net is a geometry-aware neural network for motion estimation in videos.
From two video frames, the CNN can regress scene depth, camera rotation+translation, motion masks, and 3D rigid rotations and translations.
These can be backprojected into 3D scene flow and 2D optical flow for frame interpolation.