  Despite progress in vision-based inspection algorithms, real-world industrial
challenges -- specifically in data availability, quality, and complex
production requirements -- often remain under-addressed. We introduce the
VISION Datasets, a diverse collection of 14 industrial inspection datasets,
uniquely poised to meet these challenges. Unlike previous datasets, VISION
brings versatility to defect detection, offering annotation masks across all
splits and catering to various detection methodologies. Our datasets also
feature instance-segmentation annotation, enabling precise defect
identification. With a total of 18k images encompassing 44 defect types, VISION
strives to mirror a wide range of real-world production scenarios. By
supporting two ongoing challenge competitions on the VISION Datasets, we hope
to foster further advancements in vision-based industrial inspection.
