1 小目标检测：
综述：
综述论文Augmentation for small object detection
深度学习笔记（十）Augmentation for small object detection（翻译）
吴建明wujianning：小目标检测的增强算法
机器之心：什么是小样本学习？这篇综述文章用166篇参考文献告诉你答案
2 目标检测
论文追踪：https://github.com/amusi/awesome-object-detection
综述文章：
1） Object Detection in 20 Years: A Survey
论文下载：https://arxiv.org/abs/1905.05055
论文阅读：论文笔记-2019-Object Detection in 20 Years: A Survey
2）A Survey of Deep Learning-based Object Detection
论文下载：https://arxiv.org/abs/1907.09408
论文阅读：墨仆：读 A Survey of Deep Learning-based Object Detection
3）Recent Advances in Deep Learning for Object Detection
论文下载：https://arxiv.org/abs/1908.03673
论文阅读：一个啥都不会的程序猿：目标检测综述-Deep Learning for Object Detection（一）
4）Deep Learning for Generic Object Detection: A Survey
论文下载：Deep Learning for Generic Object Detection: A Survey
论文阅读：Deep Learning for Generic Object Detection: A Survey -- 目标检测综述总结
跑者小越：私藏多年的目标检测好文分享 (不收藏血亏)
3 数据增强
chaser：A survey on Image Data Augmentation 数据增强文献综述
CrazyVertigo：数据增强方法
CrazyVertigo：GridMask Data Augmentation
https://github.com/CrazyVertigo/awesome-data-augmentationTom Hardy：汇总|目标检测中的数据增强、backbone、head、neck、损失函数4 卷积神经网络
1）
论文地址：https://arxiv.org/abs/1803.08834
94页论文综述卷积神经网络：从基础技术到研究前景
2）A Survey of the Recent Architectures of Deep Convolutional Neural Networks
论文阅读：Deep learning_CNN_Review：A Survey of the Recent Architectures of Deep Convolutional Neural Networks--2019
论文下载：A Survey of the Recent Architectures of Deep Convolutional Neural Networks
5 类别不均衡
ChenJoya：Imbalance Problems in Object Detection: A Review
https://github.com/kemaloksuz/ObjectDetectionImbalance
鑫鑫淼淼焱焱：类别不平衡学习资源推荐
ZhiningLiu1998/awesome-imbalanced-learning
6 关于深度学习优化方法
1）https://mp.weixin.qq.com/s/hbJjWah8pzT3PskwqTCUkQ
2）链接:https://pan.baidu.com/s/1DCQYTfG5deU4zTIrJcuLSQ 密码:x22d
7 NMS
Adaptive NMS: Refining Pedestrian Detection in a Crowd
论文阅读：论文阅读2(CVPR2019):Adaptive NMS:Refining Pedestrian Detection in a Crowd
论文下载：Adaptive NMS: Refining Pedestrian Detection in a Crowd
8 模型训练
1) Bag of Freebies for Training Object Detection Neural Networks
论文下载：Bag of Freebies for Training Object Detection Neural Networks
论文阅读：
李沐等将目标检测绝对精度提升 5%，不牺牲推理速度
9 目标检测中attention
1）Relation Networks for Object Detection
论文阅读：Relation Networks for Object Detection算法笔记
论文下载；Relation Networks for Object Detection
10)IoU
CrazyVertigo：目标检测回归损失函数简介：SmoothL1/IoU/GIoU/DIoU/CIoU Loss
11)模型加速
CrazyVertigo：【模型压缩和加速】inception/mobilenet/squeezenet/shuffle
简枫：一文看懂深度学习模型压缩和加速
12）实验效率及可视化
LiuFG：提高DL实验效率神器初体验-fitlog/nni/determind13）小目标学习
14）目标检测tricks
https://zhuanlan.zhihu.com/p/141878389
初识CV：目标检测比赛中的tricks（已更新更多代码解析）
roger：目标检测中的Tricks
未完待续！！！
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