---
author:
- |
    Yana Hasson^1,2^ [^1] Bugra Tekin^4^ Federica Bogo^4^\
    Ivan Laptev^1,2^ Marc Pollefeys^3,4^ Cordelia Schmid^1,5^\
    \
    [^1^Inria, ^2^Département d’informatique de l’ENS, CNRS, PSL Research University]{}\
    [^3^ETH Zürich, ^4^Microsoft]{}, [^5^Univ. Grenoble Alpes, CNRS, Grenoble INP, LJK]{}
bibliography:
- 'egbib.bib'
title: |
    Leveraging Photometric Consistency over Time for\
    Sparsely Supervised Hand-Object Reconstruction
---

Appendix {#appendix .unnumbered}
========

Our main paper described a method for joint reconstruction of hands and objects, and proposed to leverage photometric consistency as an additional source of supervision in scenarios where ground truth is scarce. We provide additional details on the implementation in Section \[sec:implemdetails\], and describe the used training and test splits on the HO-3D dataset [@hampali2019ho3d] in Section \[sec:ho3dsub\]. In Section \[sec:cyclic\], we detail the cyclic consistency check that allows us to compute the valid mask for the photometric consistency loss. Section \[sec:skeletonadapt\] provides additional insights on the effect of using the skeleton adaptation layer.

[^1]: This work was performed during an internship at Microsoft.
