形变目标识别DPM论文《Object Detection with Discriminatively Trained Part Based Models》阅读笔记
DPM论文阅读笔记 DPM（Deformable Parts Model）本质上是“整体HOG+组件HOG+SVM”进行目标识别，其识别效果非常好。但是在具体如何选择合适的训练集、剪切目标区域、合理设置参数等并不是很清楚。所谓“知其然，知其所以然”，所以决定研究一下DPM算法。 我主要以《Object Detectionwith Discriminatively T
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相关文章
- 1. Discriminatively Trained Deformable Part Models
- 2. 论文阅读Domain Adaptation of DPM models
- 3. 目标检测之LibPaBOD（a LIBrary for PArt-Based Object Detection in C++）
- 4. Knowledge Distillation论文阅读（2）：Learning Efficient Object Detection Models with Knowledge Distillation
- 5. 1707.ICCV.Neural Person Search Machines检测加识别 论文阅读笔记
- 6. part-aligned系列论文：1711.Beyond Part Models- Person Retrieval with Refined Part Pooling 论文阅读笔记
- 7. 论文阅读：EfficientDet: Scalable and Efficient Object Detection
- 8. 论文：Training Region-based Object Detectors with Online Hard Example Mining 阅读笔记
- 9. 论文阅读笔记《Few-Example Object Detection with Model Communication》
- 10. End-to-End Object Detection with Transformers论文阅读笔记