AgriVision: A Benchmark Dataset for Advancing Real-World Robotic Vision in Densely Fruited Blueberry Crop

We introduce a comprehensive large-scale dataset repository for dense blueberry crop analysis, comprising three subsets aimed at advancing learning paradigms in this domain: DB-1) 1,195 fully annotated high-resolution images for supervised learning, DB-2) 141K frames from 520 videos for weakly/semi-supervised learning, and DB-3) 10K synthetic images with annotations, generated via our proposed data realization algorithm that mimics real-field complexity by offering a scalable, cost-effective foundation for dense crop annotation and robust model generalization.