Canva implemented a scalable similar-image replacement system using reverse image search to maintain their high-quality image library. This involved selecting a model for image embeddings, experimenting with five high-performing models, and ultimately choosing DINOv2 for its superior results in preserving image subjects and

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Table of contents
Image similarityDesign considerations and requirementsImage embeddingsVector databaseResultsUser interfaceFuture workConclusionAdditional model comparison examplesAcknowledgements

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