You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
To train or evaluate the (trained/downloaded) models, it is first required to download the SUNCG dataset and preprocess the data and download the splits here. Please see the detailed README files for Training or Evaluation of models for subsequent instructions. Please note that these splits are different than the splits used by Factored3d
To train or evaluate on the NYUv2 dataset the (trained/downloaded) models, it is first required to download the NYU dataset and preprocess the data and download the splits here. Please see the detailed README files for Training or Evaluation of models for subsequent instructions.
Citation
If you use this code for your research, please consider citing:
@article{kulkarni20193d,
title={3D-RelNet: Joint Object and Relational Network for 3D Prediction},
author={Kulkarni, Nilesh
and Misra, Ishan
and Tulsiani, Shubham
and Gupta, Abhinav},
journal={International Conference on Computer Vision (ICCV)}
year={2019}
}
About
Code release for "3D-RelNet: Joint Object and Relation Network for 3D prediction"