From 90bafdbd844b9984b096fd3bd5851ad6d0ac642d Mon Sep 17 00:00:00 2001 From: Simon Meister Date: Mon, 6 Nov 2017 13:56:27 +0100 Subject: [PATCH] Update approach.tex --- approach.tex | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/approach.tex b/approach.tex index 451faf4..2c9d9e5 100644 --- a/approach.tex +++ b/approach.tex @@ -89,7 +89,7 @@ predict $\sin(\alpha)$, $\sin(\beta)$, $\sin(\gamma)$ and $t_t^{cam}$ in the sam \subsection{Supervision} -\paragraph{Per-RoI supervision with motion ground truth} +\paragraph{Per-RoI supervision with 3D motion ground truth} The most straightforward way to supervise the object motions is by using ground truth motions computed from ground truth object poses, which is in general only practical when training on synthetic datasets. @@ -124,7 +124,7 @@ We supervise the camera motion with ground truth analogously to the object motions, with the only difference being that we only have a rotation and translation, but no pivot term for the camera motion. -\paragraph{Per-RoI supervision \emph{without} motion ground truth} +\paragraph{Per-RoI supervision \emph{without} 3D motion ground truth} A more general way to supervise the object motions is a re-projection loss similar to the unsupervised loss in SfM-Net \cite{SfmNet}, which we can apply to coordinates within the object bounding boxes,