Working on a visual similarity search system where users upload images to find similar items in a product database. What I’ve tried: - OpenAI text embeddings on product descriptions - DINOv2 for visual features - OpenCLIP multimodal approach - Vector search using Qdrant Results are decent but not great - looking to improve accuracy. Has anyone worked on similar image retrieval challenges? Specifically interested in: - Model architectures that work well for product similarity - Techniques to improve embedding quality - Best practices for this type of search Any insights appreciated!
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