2021
DisUnknown: Distilling Unknown Factors for Disentanglement Learning
ICCV 2021poster
Disentangling data into interpretable and independent factors is critical for controllable generation tasks. With the availability of labeled data, supervision can help enforce the separation of specific factors as expected. However, it is often expensive or even impossible to label every single fac…