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Learning Independent Object Motion from Unlabelled Stereoscopic Videos: Difference between revisions
Learning Independent Object Motion from Unlabelled Stereoscopic Videos (view source)
Revision as of 19:57, 3 June 2020
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* 3D flow fields \(F = \{F^1,..., F^j\}\) | * 3D flow fields \(F = \{F^1,..., F^j\}\) | ||
* Instance masks \(M=\{M^1,..., M^j\}\) | * Instance masks \(M=\{M^1,..., M^j\}\) | ||
* For each region of interest RoI, predict a per-object flow map using a RCNN | |||
** Also predict a object mask for each RoI | |||
* Construct a full 3D scene flow map using the per-object flow maps. | |||
===Self Supervision and Loss Functions=== | |||
* View Synthesis | |||
* Geometric consistency: The depth values of the warped image and the reference image should match | |||
* Left Right consistency \(L^{lr}\) | |||
* RoI Loss \(L^{roi}\) | |||
* Full image based loss \(L^{t}\) | |||
==Architecture== | ==Architecture== | ||