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Instance Segmentation MCQ
Separate objects of the same class with distinct masks; two-stage Mask R-CNN style heads and alignment tricks.
Mask
Per object
Box
Proposal
ROIAlign
No quantize
AP_mask
IoU
Instance segmentation
Each object instance gets its own mask—even if two people share the class “person.” Often built on top of strong object detectors with a parallel mask branch.
Mask R-CNN
Faster R-CNN backbone + FPN + class/box head + small FCN per ROI to predict a fixed-resolution binary mask.
Details
ROIAlign
Bilinear sampling without harsh quantization—fixes misalignment vs ROI pooling for masks.
AP_mask
Average precision over mask IoU thresholds—COCO-style reporting.
vs semantic
Semantic merges same-class instances; instance keeps them separate.
Alternatives
One-stage instance (YOLACT), query-based (Mask2Former)—tradeoffs in speed vs accuracy.
Output
N instances: class, box, binary mask per instance