ReLEAP: Upcycling Vision Datasets through Cross-Task Unification and Semi-Supervised Annotation

ReLEAP is a Python framework that unifies heterogeneous image datasets by abstracting data sources, reusing annotations across tasks, and mapping labels to a shared taxonomy. The authors demonstrate its use in precision agriculture, integrating fifteen datasets of plant species and annotation types, and show that unified data and annotation upcycling improve training data availability and transparency. They also conduct cross-dataset experiments to explore how domain-specific and foundation models can generate higher-level annotations in unsupervised, weakly supervised, and semi-supervised settings.

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