"Understanding Bayesian rooms using composite 3D object models", by Luca Del Pero, Joshua Bowdish, Emily Hartley, Bonnie Kermgard, and Kobus Barnard, CVPR 2013
This material is based upon work supported by the National Science Foundation under Grant No. 0747511. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
The ground truth data available here is for the UCB dataset (available here, and mirrored here) and for the test split of the Hedau dataset (available here).
Ground truth object masks not including chairs:
Masks for the UCB dataset (Same data used for our
CVPR 2012 paper )
Masks for the Hedau dataset
Ground truth object masks for chairs:
Masks for the UCB dataset
Masks for the Hedau dataset
Ground truth orientation maps for evaluating on room layout (room box) error:
UCB dataset
Hedau dataset
More extensive data for indoor scence understanding is available here.