Research map / Detection and segmentation / CNN features
FastMask: Segment Multi-Scale Object Candidates in One Shot
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add a residual component to the average-pooling neck (ablation) | FastMask · COCO | AR@100: 27.9 -> 29.3 | Helped |
| use max pooling instead of the residual neck (ablation) | FastMask · COCO | AR@100: 29.3 -> 27.8 | Hurt |
| use a feed-forward neck instead of the residual neck (ablation) | FastMask · COCO | AR@100: 29.3 -> 27.1 | Hurt |
| add spatial attention to the decoding head (ablation) | FastMask · COCO | AR@100: 24.8 -> 29.3 | Helped |
| add spatial attention to the decoding head (ablation) | FastMask · COCO | AR@10: 12.7 -> 15.2 | Helped |
| reduce the feature pyramid from 8 scales to 4 (ablation) | FastMask · COCO | AR@100: 31.3 -> 26.6 | Hurt |
| reduce the feature pyramid from 8 scales to 4 (ablation) | FastMask · COCO | Speed: 0.26s -> 0.14s | Helped |
| use a two-stream feature pyramid rather than image-pyramid inference | FastMask · COCO segmentation proposals | Speed: 0.46s -> 0.26s | Helped |
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