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.

#machine learning #tensorflow #visualization #cloudaae: learning 6d object pose regression with on-line data synthesis on point clouds #cloudaae #learning 6d