Selective segmentation with MC Dropout

A U-Net labels every pixel of a pet photo as pet, background or border (the outline). It runs 21 times in your browser: once normally and 20 times with random dropout. Where the 20 dropout runs disagree, the model is unsure and abstains (red). Lower coverage means it answers on fewer pixels but makes fewer mistakes.

Pixel error 8.13% → 2.18% at 80% coverage Selective mIoU 0.777 → 0.882 Oxford-IIIT Pet, 3,669 test images

Input

Output

Input
Prediction
Uncertainty (brighter = less sure)
Kept answers (red = abstained)
pet background border abstained
Loading model (31 MB, once)…