Content Based Image Retrieval

Content-Based Image Retrieval (CBIR) is a classic problem in computer vision, primarily divided into two categories: category-level retrieval and instance-level retrieval. Category-level retrieval aims to find all images within a dataset that belong to the same category as the query image, while instance-level retrieval focuses on identifying the exact specific instance that matches the query image. This technology holds significant application value in areas such as image search engines, intelligent photo management, and e-commerce.