This is an implementation of Recurrent BIM-PoseNet for camera pose regression related to our upcoming work. More details will be available soon.
The initial weight file (GoogleNet V1 trained on the Places dataset) can be found here.
The training and the test data can be found in this repository.
If you are using the dataset or any part of the code, please cite our works:
- Acharya, D., Khoshelham, K., and Winter, S., 2019. BIM-PoseNet: Indoor camera localisation using a 3D indoor model and deep learning from synthetic images. ISPRS Journal of Photogrammetry and Remote Sensing. 150: 245-258.
- Acharya, D., Singha Roy, S., Khoshelham, K. and Winter, S. 2019. Modelling uncertainty of single image indoor localisation using a 3D model and deep learning. In ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences, IV-2/W5, pages 247-254.