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  • 深度学习目标检测算法综述(论文和代码)

    RCNN-→SPP Net-→ Fast RCNN-→ Faster RCNN-→ YOLO-→ SSD

    思路是:a,生成候选框 bCNN提取特征 c,分类网络 d,回归,位置精修(refine)

    RCNN:

    论文:

    https://arxiv.org/pdf/1311.2524.pdf

    源码:

    https://github.com/rbgirshick/rcnn

    一些解读:

    https://blog.csdn.net/shenxiaolu1984/article/details/51066975

    https://blog.csdn.net/hjimce/article/details/50187029

    https://blog.csdn.net/tsq292978891/article/details/78722813

    SPP Net:

    论文:

    https://arxiv.org/pdf/1406.4729.pdf

    源码:

    caffe spp layer:https://blog.csdn.net/u013010889/article/details/53928363

    一些解读:

    https://zhuanlan.zhihu.com/p/27485018

    Fast RCNN

    论文:

    https://arxiv.org/pdf/1504.08083.pdf

    源码:

    https://github.com/rbgirshick/fast-rcnn

    一些解读:

    https://blog.csdn.net/shenxiaolu1984/article/details/51036677

    Faster RCNN

    论文:

    https://arxiv.org/pdf/1506.01497.pdf

    源码:

    https://github.com/rbgirshick/py-faster-rcnn

    一些解读:

    https://blog.csdn.net/shenxiaolu1984/article/details/51152614

    https://blog.csdn.net/u013010889/article/details/78574879

    https://zhuanlan.zhihu.com/p/31426458

    YOLO/YOLO.V2

    论文:

    https://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Redmon_You_Only_Look_CVPR_2016_paper.pdf

    https://arxiv.org/pdf/1612.08242.pdf

    源码:

    https://github.com/pjreddie/darknet 

    一些解读:

    https://blog.csdn.net/ben_ben_niao/article/details/52014285

    https://blog.csdn.net/u014380165/article/details/72616238

    https://blog.csdn.net/jesse_mx/article/details/53925356

    SSD

    论文:

    https://arxiv.org/abs/1512.02325

    源码:

    https://github.com/weiliu89/caffe/tree/ssd

    一些解读:

    https://www.cnblogs.com/fariver/p/7347197.html

    整个系列总结:

    https://blog.csdn.net/linolzhang/article/details/54344350

    https://wenku.baidu.com/view/cb977f29f68a6529647d27284b73f242336c31df.html

     

     

     

     

     

     

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  • 原文地址:https://www.cnblogs.com/buyizhiyou/p/8651790.html
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