Active Visual Exploration Based on Attention-Map Entropy

Understand

Active visual exploration addresses the issue of limited sensor capabilities in real-world scenarios, where successive observations are actively chosen based on the environment.

• To tackle this problem, we introduce a new technique called Attention-Map Entropy (AME).
• It leverages the internal uncertainty of the transformer-based model to determine the most informative observations.
• In contrast to existing solutions, it does not require additional loss components, which simplifies the training.