Machine Learning

CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds

CloudAAE

This is an tensorflow implementation of “CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds”

Files

  1. log: directory to store log files during training.
  2. losses: loss functions for training.
  3. models: a python file defining model structure.
  4. object_model_tfrecord: full object models for data synthesizing and visualization purpose.
  5. tf_ops: tensorflow implementation of sampling operations (credit: Haoqiang Fan, Charles R. Qi).
  6. trained_network: a trained network.
  7. utils: utility files for defining model structure.
  8. ycb_video_data_tfRecords: synthetic training data and real test data for the YCB video dataset.
  9. evaluate_cloudAAE_ycbv.py: script for testing object 6d pose estimation with a trained network on test set in YCB video dataset.
  10. train_cloudAAE_ycbv.py: script for training a network on synthetic data for YCB objects.
  1. Testing data in tfrecord format is available

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