How I found nearly 300,000 errors in MS COCO

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Hi folks! I've made a new technique for finding errors in object detection datasets, using new explainable AI techniques from my PhD. I was frankly pretty surprised to be able to find about 275k errors in MS COCO's training set (which has around 700k labels). This includes things like incorrectly drawn bounding boxes (shown below, about 55k), missing background labels (178k), and missing labels that overlap with existing labels (40k).

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