ICCV2019 | 論文閱讀 SCRDet：Towards More Robust Detection for Small, Cluttered and Rotated Objects
SCRDet 前言 一、背景介紹 二、SCRDet算法流程 1. SF-Net 2. MDA-Net 3. Rotation Branch 三、損失函數 3.1 Loss Function 3.2 Regrssion Loss 3.3 Attention Loss 3.4 Classification Loss 四、實驗部分 4.1 DOTA Dataset 的標註格式 4.2 Visualiza
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相關文章
- 1. ICCV2019——SCRDet Towards More Robust Detection for Small, Cluttered and Rotated Objects
- 2. POLY-YOLO: HIGHER SPEED, MORE PRECISE DETECTION AND INSTANCE SEGMENTATION FOR YOLOV3論文閱讀
- 3. 論文閱讀：Learning Data Augmentation Strategies for Object Detection
- 4. 【文獻閱讀】Perceptual Generative Adversarial Networks for Small Object Detection –CVPR-2017
- 5. 論文閱讀SLPR-Sliding Line Point Regression for Shape Robust Scene Text Detection
- 6. 論文閱讀：EfficientDet: Scalable and Efficient Object Detection
- 7. 論文閱讀：Cut, Paste and Learn: Surprisingly Easy Synthesis for Instance Detection
- 8. 【轉】論文閱讀（Chenyi Chen——【ACCV2016】R-CNN for Small Object Detection）
- 9. 論文閱讀：Deep Neural Networks for Object Detection
- 10. #ICCV2019論文閱讀#Fully_convolutional_Features