ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts

• URL: http://arxiv.org/abs/2301.12276v1
• Date: Sat, 28 Jan 2023 19:14:32 GMT
• Title: ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts
• Authors: Miko{\l}aj Sacha, Dawid Rymarczyk, {\L}ukasz Struski, Jacek Tabor, Bartosz Zieli\'nski
• Abstract summary: We introduce ProtoSeg, a novel model for interpretable semantic image segmentation. To achieve accuracy comparable to baseline methods, we adapt the mechanism of prototypical parts. We show that ProtoSeg discovers semantic concepts, in contrast to standard segmentation models.
• Score: 12.959270094693254
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We introduce ProtoSeg, a novel model for interpretable semantic image segmentation, which constructs its predictions using similar patches from the training set. To achieve accuracy comparable to baseline methods, we adapt the mechanism of prototypical parts and introduce a diversity loss function that increases the variety of prototypes within each class. We show that ProtoSeg discovers semantic concepts, in contrast to standard segmentation models. Experiments conducted on Pascal VOC and Cityscapes datasets confirm the precision and transparency of the presented method.

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