Code for paper Robust LSTM-Autoencoders for Face De-Occlusion in the Wild by Fang Zhao, Jiashi Feng, Jian Zhao, Wenhan Yang, Shuicheng Yan; TIP 2018.
To compile cudamat library, modify CUDA_ROOT
in cudamat/Makefile
to the relevant cuda root path.
Next compile .proto file by calling
protoc -I=./ --python_out=./ config.proto
lstm_ae_spatial_mr_com.py: training and test for the RLA model described in the paper.
lstm_ae_spatial_mr_com_ladv.py: training and test for the Identity Preserving RLA (IP-RLA) model described in the paper.