[P] How I fixed over 50 label issues in a popular semantic segmentation dataset

Hi folks! I've made a new technique for finding errors in semantic segmentation datasets, using new explainable AI techniques from my PhD. I was frankly pretty surprised to be able to find over 50 different error patterns , and 7% of total pixels labelled incorrectly, in MIT ADE20K (one of the most widely used segmentation datasets). In the corrected dataset, some of the less common classes are tripled in size.

While there's been some work on improving ML datasets generally, …

dataset machinelearning popular segmentation semantic