History of Face Recognition: Part 2
Face recognition has been pivotal in shaping today’s representation learning paradigm. You may not realize it, but when using Retrieval-Augmented Generation (RAG) for tasks like finding similar documents, you’re leveraging technology rooted in early face-recognition methods. In this series, we’ll journey through the breakthroughs in face-recognition technology from 2014 to 2024.
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DeepID and CasiaWebFace Innovations.
Series Introduction
Face recognition has been pivotal in shaping today’s representation learning paradigm. You may not realize it, but when using Retrieval-Augmented Generation (RAG) for tasks like finding similar documents, you’re leveraging technology rooted in early face-recognition methods — even though they apply to different modalities like images and text. This involves two steps:
- Creating embeddings: Transforming high-dimensional inputs into compact numerical vectors for similarity comparisons.
- Utilizing vector databases: Efficiently searching through millions of entries to find the closest matches.
