论文SDP + RCNN | Exploit All the Layers: Fast and Accurate CNN Object Detector with SDP and CRC
Abstract 本文提出了两种目标检测的措施，兼具精度与效率：1.scale-dependent pooling （精度）2. layer wise casaded rejection classifiers（效率） 1 Introduction 首先作者简要介绍了RCNN等方法，FRCNN的缺点： 1. Fast-RCNN由于是从pooling层bounding box所以不能准确的识别小物体
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相关文章
- 1. Exploit All the Layers: Fast and Accurate CNN Object Detector with SDP and CRC
- 2. Exploit All the Layers: Fast and Accurate CNN Object Detector with Scale Dependent Pooling and Casca
- 3. [论文解读]Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty
- 4. 论文：Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomo
- 5. 论文解读：R-CNN《Rich feature hierarchies for accurate object detection and semantic segmentation》
- 6. RCNN、SPPnet、Fast-RCNN 论文学习笔记
- 7. 《Receptive Field Block Net for Accurate and Fast Object Detection》论文笔记
- 8. 论文阅读：Fast R-CNN
- 9. Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomo
- 10. 论文《Fast and Accurate Entity Recognition with Iterated Dilated Convolutions》