New!!!

We have released a PyTorch implementation of the method for relative camera pose estimation. The code and pre-trained models are available at https://github.com/AaltoVision/RelPoseNet

Relative camera pose estimation using CNNs

Torch code and models for Relative Camera Pose Estimation Using Convolutional Neural Networks

https://arxiv.org/abs/1702.01381

Running the code

• First, you need to download original DTU dataset (136Gb) http://roboimagedata.compute.dtu.dk/. It can be done by using the following command:

wget http://roboimagedata2.compute.dtu.dk/data/MVS/Cleaned.zip

• Inside pre-trained/ folder run download_models.sh script downloading pre-trained HybridCNN (http://places.csail.mit.edu/) model. It is needed only for training the proposed model
• And finally

th main.lua -do_evaluation -source_image_path <path/to/DTU/Cleaned> -weights ./pre-trained/siam_hybridnet_fullsized.t7

Bibtex

@inproceedings{Melekhov2017relativePoseCnn,
    author = {Iaroslav Melekhov and Juha Ylioinas and Juho Kannala and Esa Rahtu},
    title = {Relative Camera Pose Estimation Using Convolutional Neural Networks},
    url = {https://arxiv.org/abs/1702.01381},
    year = {2017}}