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Real-Time 6DOF Pose Relocalization for Event Cameras with Stacked Spatial LSTM Networks - CVPRW19
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dataset_script
main_keras
LICENSE
README.MD
__init__.py

README.MD

Requirements

  • Keras 2.0.3
  • Tensorflow >= 1.0 (used 1.1.0)

Download dataset

Create train/test data

  • cd dataset_script
  • python CREATE_DATA.py
  • change list_scene inside CREATE_DATA.py for other scene

Run train script:

  • cd main_keras
  • python train.py --gpu GPU_ID --scene SCENCE_ID
  • For example: python train.py --gpu 0 --scene shapes_rotation --> will train on GPU 0 and shapes_rotation sequence

Predict & evaluate

  • cd main_keras
  • python predict.py
  • Change in_scene_id, in_net_id, in_model_file_name in this file for different scene

If you find this code useful in your research, please consider citing:

@article{nguyen6dof_lstmpose,
  author    = {Anh Nguyen and
			   Thanh{-}Toan Do and
			   Darwin G. Caldwell and
			   Nikos G. Tsagarakis},
  title     = {Real-Time Pose Estimation for Event Cameras with Stacked Spatial {LSTM}
			   Networks},
  journal   = {IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year      = {2019}
 }
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