My Network is rather predicts the mean output instead of individual predictions
According to Page 8 of the Paper, the output of the network is the mean Heart Rate. The output is computed with a mean pooling layer. Maybe you can get the single values from the single heart rates before the mean pooling layer?
I am currently working on my Bachelor Thesis. I want to predict the heartrate of people with video data. I build my network similar to the paper "RhythmNet: End-to-End Heart Rate Estimation
From Face via Spatial-Temporal Representation".
My problem:
My network does not learn to predict the HR properly instead it learns the mean HR. Could you give me some tipps how to improve the variety of my Regression output? Do you have some general tipps how to improve the network performance?
Thx in advance