Closed carltaddybearzz closed 4 years ago
@carltaddybearzz 1. I have uploaded my 3-fold data partition into https://github.com/sharpstill/AU_R-CNN/tree/master/necessary_train_files_for_AU_R-CNN/BP4D_3_fold and https://github.com/sharpstill/AU_R-CNN/tree/master/necessary_train_files_for_AU_R-CNN/DISFA_3_fold
Closing now
First of all, thanks for sharing your code!! I have a question about the data list you provided. For BP4D, is the subjects partition same as DRML which detailed here? You are not using the data list provided here, right? Since the later one seems to be unbalanced for different folds. BTW, according to the results from your paper and this one, pre-trained VGG and ResNet can actually achieve ~60 F1 on [BP4D, same partition, frame based detections], which is consistent with my experiments. Originally I thought there were some issues with my implementations since those baselines seem to be as good as some latest conference papers.