Which of the following statement is true about Mask R-CNN? Select ALL that apply.

Question

BlackTom AI · Accepted Answer

Let's examine each statement in turn and evaluate its accuracy based on how Mask R-CNN works and how RoI features are used in related architectures.
Option 1: "Mask R-CNN improves efficiency by reducing the number of bounding boxes for each object." This is not a core claim of Mask R-CNN. Mask R-CNN adds a mask head on top of the Faster R-CNN framework and uses a Region Proposal Network (RPN) to propose a set of candidate bounding boxes. It does not fundamentally reduce the number of bounding boxes per object, nor does it claim a more efficient per-object bounding box reduction as its primary advantage. Therefore this statement is misleading and generally considered false in the context of Mask R-CNN.
Option 2: "Mask R-CNN outputs oriented instead of axis-aligned bounding boxes." Mask R-CNN outputs axis-aligned bounding boxes around instances, not oriented (rotated) boxes. The orientation or rotation would require a different representation or specific rotation-aware variants. Thus this statement is false.
Option 3: "Mask R-CNN makes pixel-wise binary detections for objects." This is true. A distinctive feature of Mask R-CNN is the parallel mask branch that predicts a binary mask (per instance) at the pixel level, enabling pixel-precise segmentation in addition to bounding boxes and class scores. This aligns with the core design of Mask R-CNN.
Option 4: "Both Mask R-CNN and Faster R-CNN use RoI Align." Here the nuance matters. RoI Align was introduced to replace RoI Pooling in Mask R-CNN to avoid quantization issues when extracting features for proposals. While Mask R-CNN uses RoI Align, the classic Faster R-CNN pipeline originally used RoI Pooling, not RoI Align. Some later implementations and papers adopt RoI Align more broadly, but the statement as a blanket claim that both always use RoI Align is not strictly correct for the original Faster R-CNN setup. Therefore this statement is false in the strict sense.
In summary, only the third option accurately describes a true feature of Mask R-CNN, while the others contain inaccuracies or misleading claims about efficiency, bounding box orientation, or RoI feature usage. However, if your course or textbook specifies a broader adoption of RoI Align across variants of Faster R-CNN, you might encounter a different interpretation; based on the standard definitions, option 3 is the correct one here.

ROB 498 004 WN 2025 20250219 Object Detection 2 Quiz

Which of the following statement is true about Mask R-CNN? Select ALL that apply.

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