【Distill 系列：二】CVPR 2019 Distilling Object Detectors with Fine-grained Feature Imitation

時間 2021-01-13

標籤 Model Compression 简体版

原文原文鏈接

cvpr 2019 detectors care more about local near object regions motivation Fitnets: Hints for thin deep nets hint learning 利用網絡中間層 teacher & student feature map L2 loss 分析 feature map 整體做 hint 不好，detect

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1. Distilling Object Detectors with Fine-grained Feature Imitation
2. CVPR 2017:Large Margin Object Tracking with Circulant Feature Maps
3. Training Region-based Object Detectors with Online Hard Example Mining
4. 【Distill 系列：一】bmvc2019 Learning Efficient Detector with Semi-supervised Adaptive Distillation
5. OHEM：Training Region-based Object Detectors with Online Hard Example Mining
6. one-stage object detectors(1)
7. 2019 CVPR之ReID：Towards Rich Feature Discovery with Class Activation Maps Augmentation for Person Re-
8. 【FPN】《Feature Pyramid Networks for Object Detection》
9. 論文閱讀：DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution
10. CVPR 2020-Object Detection
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1. Distilling Object Detectors with Fine-grained Feature Imitation
2. CVPR 2017:Large Margin Object Tracking with Circulant Feature Maps
3. Training Region-based Object Detectors with Online Hard Example Mining
4. 【Distill 系列：一】bmvc2019 Learning Efficient Detector with Semi-supervised Adaptive Distillation
5. OHEM：Training Region-based Object Detectors with Online Hard Example Mining
6. one-stage object detectors(1)
7. 2019 CVPR之ReID：Towards Rich Feature Discovery with Class Activation Maps Augmentation for Person Re-
8. 【FPN】《Feature Pyramid Networks for Object Detection》
9. 論文閱讀：DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution
10. CVPR 2020-Object Detection

>>更多相關文章<<