CBIR research platform
A content-based image retrieval workflow built around modern vision models, developed as applied computer-vision research.
- Python
- Computer vision
- Self-supervised learning
Context
Part of research into content-based image retrieval (CBIR) and self-supervised vision representations — using a model's learned image representations to find visually or semantically similar images rather than relying on manual tags.
Problem
Keyword and tag-based image search misses results that are visually or conceptually similar but not labeled the same way.
Approach
Applied self-supervised and modern vision models to generate image representations, then built a retrieval workflow around them to test retrieval quality.
Main capabilities
- Image-similarity search based on learned visual representations
- Experimentation pipeline for evaluating different vision models
Outcome / current status
Research project; not packaged as a client-facing product.
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