文章目录
- 一、基于特征金字塔
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- 1.1 FPN：Feature Pyramid Networks for Object Detection
- 1.2 RetinaFace: Single-stage Dense Face Localisation in the Wild
- 1.3 SSH: Single Stage Headless Face Detector
- 二、FPN魔改版
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- 2.1 Path aggregation network for instance segmentation CVPR 2018
- 2.2 Augfpn: Improving multi-scale feature learning for object detection CVPR 2020
- 2.3 Effective fusion factor in fpn for tiny object detection WACV 2021
- 三、基于感受野
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- 3.1 Scale-Aware Trident Networks for Object Detection ICCV 2019
- 四、基于GAN
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- 4.1 SOD-MTGAN: Small Object Detection via Multi-Task Generative Adversarial Network ECCV 2018
- 4.2 Perceptual Generative Adversarial Networks for Small Object Detection CVPR 2017
- 4.3 Better to Follow, Follow to Be Better: Towards Precise Supervision of Feature Super-Resolution for Small Object Detection ICCV 2019
- 五、基于Context信息
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- 5.1 PyramidBox: A Context-assisted Single Shot Face Detector
- 5.2 Relation Networks for Object Detection
- 5.3 Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks CVPR 2016
- 六、基于Data
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- 6.1 Stitcher: Feedback-driven Data Provider for Object Detection CVPR 2020
- 6.2 Augmentation for small object detection CVPR 2019
- 七、特殊训练策略
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- 7.1 An Analysis of Scale Invariance in Object Detection – SNIP CVPR 2018
- 7.2 SNIPER: Efficient Multi-Scale Training NIPS 2018
- 7.3 R-FCN: Object Detection via Region-based Fully Convolutional Networks
- 7.4 SAN: Learning Relationship between Convolutional Features for Multi-Scale Object Detection
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