Explicitly Disentangled Representations in Object-Centric Learning

Understand

Extracting structured representations from raw visual data is an important and long-standing challenge in machine learning.

• Recently, techniques for unsupervised learning of object-centric representations have raised growing interest.
• In this context, enhancing the robustness of the latent features can improve the efficiency and effectiveness of the training of downstream tasks.
• A promising step in this direction is to disentangle the factors that cause variation in the data.