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R-FCN++: Towards Accurate Region-Based Fully Convolutional Networks for Object Detection
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add GCM with kernel size 15 to R-FCN (ablation) | R-FCN · VOC2007 test | mAP: 79.1 -> 80.7 | Helped |
| add RCMPooling instead of PSPooling (ablation) | R-FCN · VOC2007 test | mAP: 79.1 -> 79.6 | Helped |
| add RCMPooling on top of GCM (ablation) | R-FCN+GCM · COCO minival | AP: 29.5 -> 30.4 | Helped |
| enlarge GCM kernel size from 1 to 15 (ablation) | GCM · VOC2007 test | mAP: 79.1 -> 80.7 | Helped |
| replace separable GCM with naive kxk conv (ablation) | GCM · VOC2007 test | mAP: 80.6 -> 80.6 (k=9) | No clear effect |
| use stack of 3x3 convs instead of large kernel (ablation) | GCM · VOC2007 test | mAP: 80.6 -> 79.7 (k=9) | Hurt |
| reduce middle channels to 64 (Light-GCM) (ablation) | GCM · VOC2007 test | mAP: 80.7 -> 80.3 | Hurt |
| add RCMPooling across IoU thresholds (ablation) | R-FCN · VOC2007 test, IoU 0.9 | mAP: 12.8 -> 13.6 | Helped |
| Light-GCM with ResNet-50 instead of R-FCN ResNet-101 | R-FCN++ · VOC2007 test | test time (s): 0.093 -> 0.072 | Helped |
Closest papers by meaning
- R-FCN: Object Detection via Region-based Fully Convolutional Networks (NeurIPS 2016 · similarity 0.95)
- R-FCN-3000 at 30fps: Decoupling Detection and Classification (CVPR 2018 · similarity 0.89)
- Cascade R-CNN: Delving Into High Quality Object Detection (CVPR 2018 · similarity 0.89)
- Feature Pyramid Networks for Object Detection (CVPR 2017 · similarity 0.88)
- Inside-Outside Net: Detecting Objects in Context With Skip Pooling and Recurrent Neural Networks (CVPR 2016 · similarity 0.87)
- Object Detection Based on Region Decomposition and Assembly (AAAI 2019 · similarity 0.87)
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