Research map / Detection and segmentation / Open-set and few-shot detection
Meta Faster R-CNN: Towards Accurate Few-Shot Object Detection with Attentive Feature Alignment
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Meta-RPN instead of RPN for novel-class proposal generation (ablation) | Meta Faster R-CNN · MSCOCO novel classes, 10-shot meta-testing | AP: 7.2 -> 8.3 | Helped |
| Use Meta-RPN instead of Attention-RPN (ablation) | Meta Faster R-CNN · MSCOCO novel classes, 10-shot meta-testing | AP: 7.7 -> 8.3 | Helped |
| Add spatial feature alignment (ablation) | Meta-RPN + Meta-Classifier · MSCOCO novel classes, 10-shot meta-testing | AP: 8.3 -> 8.6 | Helped |
| Add foreground attention to alignment (ablation) | Meta-RPN + Meta-Classifier · MSCOCO novel classes, 10-shot meta-testing | AP: 8.6 -> 9.2 | Helped |
| Align the class prototype to the proposal feature rather than the reverse (ablation) | Meta-Classifier · MSCOCO novel classes, 2-shot meta-testing | AP: 5.1 -> 7.0 | Helped |
| Use ResNet-101 instead of ResNet-50 (ablation) | Meta Faster R-CNN · MSCOCO novel classes, 10-shot meta-testing | AP: 9.2 -> 9.7 | Helped |
| Fine-tune the model on novel classes (ablation) | Meta Faster R-CNN · MSCOCO novel classes, 2-shot | AP: 7.0 -> 7.6 | Helped |
| Fine-tune the model on novel classes (ablation) | Meta Faster R-CNN · MSCOCO novel classes, 10-shot | AP: 9.7 -> 12.7 | Helped |
| Fine-tune the model on novel classes (ablation) | Meta Faster R-CNN · MSCOCO novel classes, 2-shot | AP: 7.0 -> 7.6 | No clear effect |
| Combine multiplication, subtraction, and concatenation feature-fusion branches (ablation) | Meta-RPN · MSCOCO novel classes, 10-shot meta-testing | AP: 7.7 -> 8.3 | Helped |
| Combine multiplication, subtraction, and concatenation feature-fusion branches (ablation) | Meta-Classifier · MSCOCO novel classes, 10-shot meta-testing | AP: 7.3 -> 8.3 | Helped |
| Replace the multiplication branch with concatenation-only fusion (ablation) | Meta-Classifier · MSCOCO novel classes, 10-shot meta-testing | AP: 7.3 -> 5.3 | Hurt |
Closest papers by meaning
- Few-Shot Object Detection with Foundation Models (CVPR 2024 · similarity 0.91)
- Fine-Grained Prototypes Distillation for Few-Shot Object Detection (AAAI 2024 · similarity 0.91)
- Weakly Supervised Few-Shot Object Detection with DETR (AAAI 2024 · similarity 0.89)
- Revisiting Few-Shot Object Detection with Vision-Language Models (NeurIPS 2024 · similarity 0.89)
- Pushing the Limit of Fine-Tuning for Few-Shot Learning: Where Feature Reusing Meets Cross-Scale Attention (AAAI 2024 · similarity 0.88)
- Multi-Perspective Data Augmentation for Few-shot Object Detection (ICLR 2025 · similarity 0.88)
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