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Proper Reuse of Image Classification Features Improves Object Detection

CVPR 2022 · Detection and segmentation › CNN features · approach: Convolution-transformer backbones · 26 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Freeze the pretrained backbone rather than fine-tune itEfficientNet-B7 + NAS-FPN on MSCOCO · MSCOCO valBox mAP: +0.9 Box mAPHelped
Freeze the pretrained backbone rather than fine-tune itEfficientNet-B7 + NAS-FPN on MSCOCO · MSCOCO valMask mAP: +0.7 Mask mAPHelped
Add Copy-Paste augmentation and freeze the pretrained backbone (ablation)EfficientNet-B7 + NAS-FPN · MSCOCO valBox mAP: 55.9 -> 57.0Helped
Freeze the pretrained backboneEfficientNet-B7 + NAS-FPN on LVIS · LVIS valBox mAP: 37.2 -> 39.4Helped
Add Copy-Paste augmentation and freeze the pretrained backbone (ablation)EfficientNet-B7 + NAS-FPN · LVIS valBox mAP: 41.6 -> 43.1Helped
Freeze the pretrained backboneResNet-101 + NAS-FPN + Cascade · MSCOCO, 600 epochsmAP: 51.1 -> 51.8Helped
Freeze the pretrained backbone (ablation)ResNet-101 + FPN · MSCOCO, 600 epochsmAP: 48.6 -> 42.1Hurt
Use a higher-capacity NAS-FPN detector rather than FPN (ablation)Frozen ResNet-101 detector · MSCOCOmAP: -6.5 -> +0.1Helped
Pretrain on JFT-300M rather than ImageNet while freezing the backbone (ablation)ResNet detectors with NAS-FPN and Cascade · MSCOCOmAP: +0.9 mAP in most casesHelped
Add residual adapters to the frozen backbone (ablation)ResNet-101 + NAS-FPN + Cascade · MSCOCOmAP: 51.8 -> 53.0Helped
Increase detector hidden representation size from 256 to 512 (ablation)Frozen ResNet-101 + FPN · MSCOCO, 72 epochsmAP: 40.9 -> 42.9Helped
Reduce RPN convolutional layers from two to one (ablation)Frozen ResNet-101 + FPN · MSCOCOmAP: 42.1 -> 41.3Hurt

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