TAFE-Net: Task-Aware Feature Embeddings for Low Shot Learning

Understand

Learning good feature embeddings for images often requires substantial training data.

• As a consequence, in settings where training data is limited (e.g., few-shot and zero-shot learning), we are typically forced to use a generic feature embedding across various tasks.
• Ideally, we want to construct feature embeddings that are tuned for the given task.
• In this work, we propose Task-Aware Feature Embedding Networks (TAFE-Nets) to learn how to adapt the image representation to a new task in a meta learning fashion.