Research map / Detection and segmentation / CNN features
A2-FPN: Attention Aggregation Based Feature Pyramid Network for Instance Segmentation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace FPN with A²-FPN | Mask R-CNN with ResNet-50 · COCO test-dev | mask AP: 2.1% | Helped |
| Replace FPN with A²-FPN | Mask R-CNN with ResNet-101 · COCO test-dev | mask AP: 1.6% | Helped |
| Replace FPN with A²-FPN | Cascade Mask R-CNN · COCO test-dev | mask AP: 2.0% and 1.7% | Helped |
| Replace FPN with A²-FPN | HTC · COCO test-dev | mask AP: 1.4% | Helped |
| Add MGC, GACARAFE, and GACAP to PAFPN (ablation) | Mask R-CNN with ResNet-50 · COCO val2017 | mask AP: 1.8% | Helped |
| Add MGC to PAFPN (ablation) | Mask R-CNN with ResNet-50 · COCO val2017 | mask AP: 1.0% | Helped |
| Add GACARAFE to PAFPN (ablation) | Mask R-CNN with ResNet-50 · COCO val2017 | mask AP: 1.3% | Helped |
| Add GACAP to PAFPN (ablation) | Mask R-CNN with ResNet-50 · COCO val2017 | mask AP: 0.6% | Helped |
| Add GCNs to A²-FPN (ablation) | A²-FPN · COCO val2017 | mask AP: 0.3% | Helped |
| Replace CARAFE with GACARAFE (ablation) | A²-FPN · COCO val2017 | mask AP: 0.3% | Helped |
| Replace CAP with GACAP (ablation) | A²-FPN · COCO val2017 | mask AP: 0.2% | Helped |
| Vary the number of context features across tested settings (ablation) | MGC · COCO val2017 | mask AP: 0.1% | No clear effect |
Closest papers by meaning
- Feature Pyramid Networks for Object Detection (CVPR 2017 · similarity 0.89)
- Construct Effective Geometry Aware Feature Pyramid Network for Multi-Scale Object Detection (AAAI 2022 · similarity 0.88)
- AugFPN: Improving Multi-Scale Feature Learning for Object Detection (CVPR 2020 · similarity 0.88)
- Panoptic Feature Pyramid Networks (CVPR 2019 · similarity 0.88)
- M2Det: A Single-Shot Object Detector Based on Multi-Level Feature Pyramid Network (AAAI 2019 · similarity 0.86)
- HS-FPN: High Frequency and Spatial Perception FPN for Tiny Object Detection (AAAI 2025 · similarity 0.84)
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