1.Pytorch中堆网络语法:《nn.moduleList 和Sequential由来、用法和实例 —— 写网络模型》
https://blog.csdn.net/e01528/article/details/84397174
2.CNN中卷积操作十大改进方向(Depth-wise/ Dilated/ Deformable/ Shuffle/ SENet etc)
https://blog.csdn.net/hongxingabc/article/details/79563525
3.写给 python 程序员的 OpenGL 教程
https://blog.csdn.net/xufive/article/details/86565130
4.Batch Normalization 学习笔记
https://blog.csdn.net/hjimce/article/details/50866313
5.《动手学深度学习-Pytorch版》
https://tangshusen.me/Dive-into-DL-PyTorch/#/
6.YOLO系列(V1-V2-V3)
https://blog.csdn.net/Zfq740695564/article/details/79754578
7.SMPL模型进阶 & SMPL模型Shape和Pose参数
https://blog.csdn.net/chenguowen21/article/details/82793994
http://wap.sciencenet.cn/blog-465130-1177111.html
8.pytorch系列10 --- 如何自定义参数初始化方式 ,apply()
https://blog.csdn.net/dss_dssssd/article/details/83990511
9.使用pytorch读取、使用预训练模型进行finetune:以Resnet-101为例
https://blog.csdn.net/AManFromEarth/article/details/81071823
10.从零开始Pytorch YOLOv3