CV论文会员2021包括2022年1月前CV论文班所有内容 部分资料文件夹未循环遍历 大小非实际大小

【更新】【尊享】ZX007 – CV论文会员2021 [124G]

┣━━0.选修 [3.1G]
┃ ┣━━神经网络基础 [785.3M]
┃ ┃ ┣━━00.资料.zip [70.6M]
┃ ┃ ┣━━1.01-神经网络基础与多层感知机-0.vep [51.8M]
┃ ┃ ┣━━2.01-神经网络基础与多层感知机-1.vep [33.7M]
┃ ┃ ┣━━3.01-神经网络基础与多层感知机-2.vep [62M]
┃ ┃ ┣━━4.01-神经网络基础与多层感知机-3.vep [30.8M]
┃ ┃ ┣━━5.01-神经网络基础与多层感知机-4.vep [86.7M]
┃ ┃ ┣━━6.02-卷积神经网络-0.vep [64.4M]
┃ ┃ ┣━━7.02-卷积神经网络-1.vep [153.2M]
┃ ┃ ┣━━8.02-卷积神经网络-2.vep [49M]
┃ ┃ ┣━━9.03-循环神经网络-0.vep.vep [45M]
┃ ┃ ┣━━10.03-循环神经网络-1.vep [80.1M]
┃ ┃ ┗━━11.03-循环神经网络-2.vep [57.9M]
┃ ┗━━opencv基础 [2.3G]
┃ ┣━━00.资料.zip [168.3M]
┃ ┣━━1.1-1图像基础知识.vep [30.3M]
┃ ┣━━2.1-2图像基础知识.vep [31.8M]
┃ ┣━━3.1-3图像基础知识.vep [79M]
┃ ┣━━4.1-4图像基础知识.vep [69.2M]
┃ ┣━━5.2-1图像基本处理.vep [70.2M]
┃ ┣━━6.2_2图像基本处理.vep [57.4M]
┃ ┣━━7.2_3图像基本处理.vep [89.1M]
┃ ┣━━8.2_4图像基本处理.vep [93.1M]
┃ ┣━━9.2_5图像基本操作_图像滤波.vep [131.9M]
┃ ┣━━10.2_6图像基本操作_图像增强.vep [112.3M]
┃ ┣━━11.2-7形态学操作_腐蚀..vep [70.3M]
┃ ┣━━12.2_8形态学操作_膨胀开运算与闭运算.vep [113.8M]
┃ ┣━━13.3_1固定阈值分割.vep [62.9M]
┃ ┣━━14.3_2自动阈值分割.vep [81.7M]
┃ ┣━━15.3_3边缘检测算子.vep [104.4M]
┃ ┣━━16.3_4连通区域_区域生长算法.vep [74.8M]
┃ ┣━━17.3_5分水岭算法图像分割.vep [71.5M]
┃ ┣━━18.4_1特征描述_HOG.vep [74.6M]
┃ ┣━━19.4_2特征描述Harris和SIFT算法.vep [46.9M]
┃ ┣━━20.4_3纹理特征LBP算法.vep [94.1M]
┃ ┣━━21.4_4模板匹配算法.vep [85.1M]
┃ ┣━━22.4_5人脸检测算法.vep [108M]
┃ ┣━━23.5_1摄像头调用和视频的读取保存.vep [208.8M]
┃ ┣━━24.5_2帧差法视频目标识别.vep [108.2M]
┃ ┗━━25.5_3光流法和背景减除法..vep [132M]
┣━━1.CV-BASELINE [8.1G]
┃ ┣━━1.视频 [8.1G]
┃ ┃ ┣━━1.CV 开班课.vep [348.8M]
┃ ┃ ┣━━2.01AlexNet-01-研究背景.vep [155.8M]
┃ ┃ ┣━━3.01AlexNet-02- 研究成果意义.vep [24M]
┃ ┃ ┣━━4.01AlexNet-03-论文结构.vep [81.1M]
┃ ┃ ┣━━5.01AlexNet-04-结构.vep [71.6M]
┃ ┃ ┣━━6.01AlexNet-05网络结构特点.vep [87.4M]
┃ ┃ ┣━━7.01AlexNet-06-训练技巧.vep [78.9M]
┃ ┃ ┣━━8.01AlexNet-07实验结果及分析.vep [95.7M]
┃ ┃ ┣━━9.01AlexNet-08-论文总结.vep [52.2M]
┃ ┃ ┣━━10.01AlexNet-09-准备工作&代码结构.vep [51M]
┃ ┃ ┣━━11.01AlexNet-10-代码结构.vep [178.1M]
┃ ┃ ┣━━12.01AlexNet-11-代码结构.vep [85.4M]
┃ ┃ ┣━━13.01AlexNet-12- 代码结构4&训练方法.vep [211.3M]
┃ ┃ ┣━━14.02VGG-01-研究背景&成果&意义.vep [48.1M]
┃ ┃ ┣━━15.02VGG-02-论文机构&摘要精读.vep [43.2M]
┃ ┃ ┣━━16.02VGG-03-结构及特点.vep [134.5M]
┃ ┃ ┣━━17.02VGG-04-训练、测试技巧.vep [147.8M]
┃ ┃ ┣━━18.02VGG-05实验结果及分析.vep [40M]
┃ ┃ ┣━━19.02VGG-06-论文总结.vep [29.6M]
┃ ┃ ┣━━20.02VGG-07-代码结构.vep [64.4M]
┃ ┃ ┣━━21.02VGG-08-代码数据集.vep [142.1M]
┃ ┃ ┣━━22.02VGG-09-代码&构建VGG模型.vep [133.2M]
┃ ┃ ┣━━23.CVbaseline 第一次直播答疑.vep [140.7M]
┃ ┃ ┣━━24.03GoogleNet-01-研究背景、成果及意.vep [28.1M]
┃ ┃ ┣━━25.03GoogleNet-02-论文摘要、图表.vep [39.8M]
┃ ┃ ┣━━26.03GoogLeNet-03-GoogLeNet结构.vep [100.1M]
┃ ┃ ┣━━27.03GoogLeNet-04-训练、测试技巧，实验结果及分析.vep [78.3M]
┃ ┃ ┣━━28.03GoogLeNet-05-稀疏结构及总结.vep [22.1M]
┃ ┃ ┣━━29.03Googlenet-06-代码结果&数据集下载.vep [130M]
┃ ┃ ┣━━30.03Googlenet-07-结构定义&基本组件.vep [86.5M]
┃ ┃ ┣━━31.03Googlenet-08数据集&构建模型.vep [95.1M]
┃ ┃ ┣━━32.04Googlenet-v2-01-论文背景.vep [38M]
┃ ┃ ┣━━33.04Googlenet-v2-02-论文结果意义泛读.vep [64.6M]
┃ ┃ ┣━━34.04Googlenet-v2-03-论文BN层.vep [58.7M]
┃ ┃ ┣━━35.04Googlenet-v2-04-结构、实验结果及分析.vep [48.9M]
┃ ┃ ┣━━36.04Googlenet-v2-05-论文总结.vep [44.6M]
┃ ┃ ┣━━37.04GoogLeNet-v2-06-代码讲解.vep [119.6M]
┃ ┃ ┣━━38.04GoogLeNet-v2-07-代码讲解.vep [102.4M]
┃ ┃ ┣━━39.04Googlenet-v2-08-代码讲解.vep [102.7M]
┃ ┃ ┣━━40.05-googlenet-v3-01-研究背景&成果&意义.vep [27.6M]
┃ ┃ ┣━━41.05-googlenet-v3-02.vep [50.6M]
┃ ┃ ┣━━42.05-googlenet-v3-03-网络设计准则&卷积分解&辅助分类.vep [57.9M]
┃ ┃ ┣━━43.05-MP4-googlenet-v3-04-特征图分辨率下降&标签平滑.vep [46.6M]
┃ ┃ ┣━━44.05-MP4-googlenet-v3-05-网络结构&实验结果.vep [51.1M]
┃ ┃ ┣━━45.05-MP4-googlenet-v3-06-论文总结.vep [40.4M]
┃ ┃ ┣━━46.05-MP4-googlenet-v3-07-代码准备.vep [125.9M]
┃ ┃ ┣━━47.05-MP4-googlenet-v3-08-网络结构代码详解.vep [183.2M]
┃ ┃ ┣━━48.05-MP4-googlenet-v3-09-模型训练&标签平滑.vep [140.4M]
┃ ┃ ┣━━49.06-ResNet-01-背景成果意义.vep [47M]
┃ ┃ ┣━━50.06-ResNet-02-论文泛读.vep [48.4M]
┃ ┃ ┣━━51.06-ResNet-03-残差结构.vep [68.1M]
┃ ┃ ┣━━52.06-ResNet-04-ResNet结构.vep [66.5M]
┃ ┃ ┣━━53.06-ResNet-05-论文总结.vep [48.9M]
┃ ┃ ┣━━54.06-ResNet-06-ResNet推理.vep [140M]
┃ ┃ ┣━━55.06-ResNet-07-ResNet结构搭建详解.vep [127.1M]
┃ ┃ ┣━━56.06-ResNet-08-ResNet20训练及实验分析.vep [150.4M]
┃ ┃ ┣━━57.cv baseline-第三场直播答疑.vep.vep [296.2M]
┃ ┃ ┣━━58.07-MP4-googlenet-v4-01-背景成果意义.vep [53.3M]
┃ ┃ ┣━━59.07-MP4-googlenet-v4-02-论文泛读.vep [76.6M]
┃ ┃ ┣━━60.07-MP4-googlenet-v4-03-inception-v4.vep [71.4M]
┃ ┃ ┣━━61.07-MP4-googlenet-v4-04-inception-resnet.vep [75.1M]
┃ ┃ ┣━━62.07-MP4-googlenet-v4-05-实验结果论文总结.vep [36.4M]
┃ ┃ ┣━━63.07-MP4-googlenet-v4-06-inceptionv4代码（上）.vep [147.5M]
┃ ┃ ┣━━64.07-MP4-googlenet-v4-07-inceptionv4代码（下）.vep [72.6M]
┃ ┃ ┣━━65.07-MP4-googlenet-v4-inception-08-resnet代码.vep [187.9M]
┃ ┃ ┣━━66.08-MP4-ResNeXt-01-背景意义成果.vep [44.8M]
┃ ┃ ┣━━67.08-MP4-ResNeXt-02-论文泛读.vep [73.4M]
┃ ┃ ┣━━68.08-MP4-ResNeXt-03-聚合变换分析.vep [68.9M]
┃ ┃ ┣━━69.08-MP4-ResNeXt-04-分组卷积与ResNeXt.vep [49.2M]
┃ ┃ ┣━━70.08-MP4-ResNeXt-05-实验结果与论文总结.vep [62.9M]
┃ ┃ ┣━━71.08-MP4-ResNeXt-06-ResNeXt50-inference.vep [121.9M]
┃ ┃ ┣━━72.08-MP4-ResNeXt-07-ResNeXt-50_32x4d-网络搭建代码详解.vep [112.6M]
┃ ┃ ┣━━73.08-MP4-ResNeXt-08-ResNeXt-29训练.vep [123.1M]
┃ ┃ ┣━━74.08-MP4-ResNeXt-09-分组卷积.vep [44M]
┃ ┃ ┣━━75.09-MP4-DenseNet-01-背景意义成果.vep [76.4M]
┃ ┃ ┣━━76.09-MP4-DenseNet-02-论文泛读..vep [46.1M]
┃ ┃ ┣━━77.09-MP4-DenseNet-03-论文图表.vep [31.2M]
┃ ┃ ┣━━78.09-MP4-DenseNet-04-基本组件1.vep [97.1M]
┃ ┃ ┣━━79.09-MP4-DenseNet-05-基本组件2.vep [70.8M]
┃ ┃ ┣━━80.09-MP4-DenseNet-06-Densenet网络结构.vep [82.2M]
┃ ┃ ┣━━81.09-MP4-DenseNet-07-实验结果及分析.vep [60.4M]
┃ ┃ ┣━━82.09-MP4-DenseNet-08-论文总结.vep [24M]
┃ ┃ ┣━━83.09-MP4-DenseNet-09-计算图与显存分析.vep [47.8M]
┃ ┃ ┣━━84.09-MP4-DenseNet-10-DenseNet-121推理.vep [101.3M]
┃ ┃ ┣━━85.09-MP4-DenseNet-11-DenseNet-121-搭建.vep [129.7M]
┃ ┃ ┣━━86.09-MP4-DenseNet-12-DenseLayer详解..vep [85.4M]
┃ ┃ ┣━━87.09-MP4-DenseNet-13-DenseNet-40-训练.vep [163.8M]
┃ ┃ ┣━━88.10-MP4-SENet-01-学习目标课程安排.vep [16.4M]
┃ ┃ ┣━━89.10-MP4-SENet-02-研究背景.vep [65.5M]
┃ ┃ ┣━━90.10-MP4-SENet-03-研究意义及成果.vep [20.2M]
┃ ┃ ┣━━91.10-MP4-SENet-04-论文结构..vep [25.7M]
┃ ┃ ┣━━92.10-MP4-SENet-05-论文图表.vep [30.7M]
┃ ┃ ┣━━93.10-MP4-SENet-06-Squeeze-Excitation..vep [51M]
┃ ┃ ┣━━94.10-MP4-SENet-07-SE-ResNet-50..vep [34.5M]
┃ ┃ ┣━━95.10-MP4-SENet-08-实验结果及分析.vep [74.7M]
┃ ┃ ┣━━96.10-MP4-SENet-09-Ablation-Study.vep [45.1M]
┃ ┃ ┣━━97.10-MP4-SENet-10-论文总结.vep [26.1M]
┃ ┃ ┗━━98.10-MP4-SENet-11-代码实现及Baseline结语..vep [172.3M]
┃ ┗━━2.资料 [0B]
┃ ┣━━01Alexnet
┃ ┣━━02VGG
┃ ┣━━03GoogLeNet
┃ ┣━━04GoogLeNet-V2
┃ ┣━━05GoogLeNet-V3
┃ ┣━━06ResNet
┃ ┣━━07GoogLeNet-V4
┃ ┣━━08ResNeXt
┃ ┣━━09densenet
┃ ┣━━10Senet
┃ ┣━━预训练模型
┃ ┗━━Kaggle猫狗大战
┣━━2.图像分割 [19G]
┃ ┣━━01.视频 [15G]
┃ ┃ ┣━━1.01mobilenet-01-背景介绍.vep [51.8M]
┃ ┃ ┣━━1.开班课直播.vep [162.8M]
┃ ┃ ┣━━1.图像分割直播答疑.vep [275.3M]
┃ ┃ ┣━━2.01FCN-01-语意分割简介.vep [63.1M]
┃ ┃ ┣━━2.图像分割7.22直播答疑.vep [533.6M]
┃ ┃ ┣━━3.01FCN-02常用数据集、指标、研究成果..vep [100.5M]
┃ ┃ ┣━━4.01FCN-03-论文摘要精读..vep [60.9M]
┃ ┃ ┣━━5.01FCN-04-论文引言、全局信息及部分信息.vep [128.6M]
┃ ┃ ┣━━6.01FCN-05-感受域&平移不变性.vep [149.9M]
┃ ┃ ┣━━7.01FCN-06-经典算法&本文算法、上采样.vep [88M]
┃ ┃ ┣━━8.01FCN-07-算法架构..vep [139.9M]
┃ ┃ ┣━━9.01FCN-08-训练技巧&实验结果及分析..vep [139.4M]
┃ ┃ ┣━━10.01FCN-09-讨论&总结.vep [19.9M]
┃ ┃ ┣━━10.02shufflenet-02-论文结构&摘要.vep [155.3M]
┃ ┃ ┣━━11.01FCN-10-代码实现.vep [76.5M]
┃ ┃ ┣━━11.02shufflenet-03-分组点卷积.vep [263.9M]
┃ ┃ ┣━━12.01FCN-11-数据预处理..vep [203.3M]
┃ ┃ ┣━━13.01FCN-12-模型搭建.vep [231.1M]
┃ ┃ ┣━━14.01FCN-13-训练、验证&预测函数搭建..vep [126.5M]
┃ ┃ ┣━━15.01FCN-14-损失函数.vep [95.2M]
┃ ┃ ┣━━16.01FCN-15-指标计算.vep [142.4M]
┃ ┃ ┣━━17.02unet-01-论文总览&摘要精读.vep [70.9M]
┃ ┃ ┣━━18.02unet-02-医学分割相关背景&取得的成果及意义.vep [75.4M]
┃ ┃ ┣━━19.02unet-03-两篇论文相互补充.vep [68.6M]
┃ ┃ ┣━━20.02unet-04-回顾医学图像分析及CNN的发展历程.vep [188.7M]
┃ ┃ ┣━━21.02unet-05-先验知识补充.vep [44.8M]
┃ ┃ ┣━━22.02unet-06-算法架构&实验结果及分析.vep [83.8M]
┃ ┃ ┣━━23.02unet-07-试验设置及结果分析.vep [41.4M]
┃ ┃ ┣━━24.02unet-08-代码精读.vep [189.3M]
┃ ┃ ┣━━25.03SegNet-01-CNN和FCN前期介绍&论文背景&研究成果及意义.vep [84M]
┃ ┃ ┣━━26.03SegNet-02-CNN和FCN论文结构&摘要精读.vep [95.5M]
┃ ┃ ┣━━27.03SegNet-03-引言.vep [237.7M]
┃ ┃ ┣━━28.03SegNet-04-引言&D补充内容.vep [90.8M]
┃ ┃ ┣━━29.03SegNet-05-相关工作.vep [232.7M]
┃ ┃ ┣━━30.03SegNet-06-算法架构.vep [49.8M]
┃ ┃ ┣━━31.03SegNet-07-算法架构2.vep [224.5M]
┃ ┃ ┣━━32.03SegNet-08-解码器变体&实验设置、分析.vep [206.6M]
┃ ┃ ┣━━33.03SegNet-09-归纳实验设置参数&总结关键点.vep [100.2M]
┃ ┃ ┣━━34.03SegNet-10-模型的搭建.vep [101.8M]
┃ ┃ ┣━━35.03SegNet-11-DeconvNet模型的搭建.vep [43.3M]
┃ ┃ ┣━━36.04DeepLab-01论文背景、研究成果及意义.vep [60M]
┃ ┃ ┣━━37.04DeepLab-02-摘要.vep [97M]
┃ ┃ ┣━━38.04DeepLab-03-v1论文精读.vep [102.9M]
┃ ┃ ┣━━39.04DeepLab-04-v1论文精读2.vep [106.8M]
┃ ┃ ┣━━40.04DeepLab-05-v1-论文精读3总结.vep [70.5M]
┃ ┃ ┣━━41.04DeepLab-06-v2论文精读1.vep [231.4M]
┃ ┃ ┣━━42.04DeepLab-07-v2-论文精读2.vep [151.1M]
┃ ┃ ┣━━43.04DeepLab-08-v2论文精读3总结.vep [97.3M]
┃ ┃ ┣━━44.04DeepLab-09-v3论文精读1.vep [176.5M]
┃ ┃ ┣━━45.04DeepLab-10-v3-算法及实验部分.vep [207.5M]
┃ ┃ ┣━━46.04DeepLab-11-论文精讲v3+.vep [113.7M]
┃ ┃ ┣━━47.04DeepLab-12-v3+深度可分离卷积.vep [110.1M]
┃ ┃ ┣━━48.04DeepLab-13-v3+算法和实验、论文总结.vep [82.4M]
┃ ┃ ┣━━49.04DeepLab-14-代码复现.vep [134.8M]
┃ ┃ ┣━━50.04DeepLab-15-算法架构.vep [175.1M]
┃ ┃ ┣━━51.05GCN-01-前期介绍、论文导读.vep [31.6M]
┃ ┃ ┣━━52.05GCN-02-卷积核、卷积方式汇总.vep [58.5M]
┃ ┃ ┣━━53.05GCN-03-卷积方式汇总、论文结果及意义.vep [93M]
┃ ┃ ┣━━54.05GCN-04-引言及相关工作.vep [146.9M]
┃ ┃ ┣━━55.05GCN-05-特性、算法架构.vep [154.4M]
┃ ┃ ┣━━56.05GCN-06-实验设置、分析.vep [47.4M]
┃ ┃ ┣━━57.05GCN-07-代码精读.vep [123M]
┃ ┃ ┣━━58.05GCN-08-代码精读2.vep [138.3M]
┃ ┃ ┣━━59.06DFN-01-前期知识、论文背景.vep [123.8M]
┃ ┃ ┣━━60.06DFN-02-研究成果及意义.vep [60.8M]
┃ ┃ ┣━━61.06DFN-03-论文结构、摘要.vep [41.4M]
┃ ┃ ┣━━62.06DFN-04-算法模型详解.vep [168M]
┃ ┃ ┣━━63.06DFN-05-算法结构1.vep [219.6M]
┃ ┃ ┣━━64.06DFN-06-算法结构2.vep [185M]
┃ ┃ ┣━━65.06DFN-07-算法模型细节.vep [27.7M]
┃ ┃ ┣━━66.06DFN-08-代码架构.vep [70M]
┃ ┃ ┣━━67.06DFN-09-模型搭建.vep [76.2M]
┃ ┃ ┣━━68.06DFN-10-代码复现.vep [51.6M]
┃ ┃ ┣━━69.07ENet-01-经典分割vs实时分割.vep [55.8M]
┃ ┃ ┣━━70.07ENet-02-实时分割常用方法&摘要精读.vep [69.9M]
┃ ┃ ┣━━71.07ENet-03-ENet引言&相关工作.vep [111.8M]
┃ ┃ ┣━━72.07ENet-04-LinkNet引言&相关工作&先验知识&ENet算法架构.vep [117.2M]
┃ ┃ ┣━━73.07ENet-05-ENet算法细节&LinkNet算法架构&实验分析.vep [202.3M]
┃ ┃ ┣━━74.07ENet-06-LinkNet代码定义.vep [80.2M]
┃ ┃ ┣━━75.07ENet-07-ENet代码定义.vep [116.1M]
┃ ┃ ┣━━76.07ENet-08-新代码(上).vep [119.4M]
┃ ┃ ┣━━77.07ENet-09-新代码(下).vep [94M]
┃ ┃ ┣━━78.08BiSeNet-01-分割常用损失函数(上).vep [60.2M]
┃ ┃ ┣━━79.08BiSeNet-02-分割常用损失函数(中).vep [51.3M]
┃ ┃ ┣━━80.08BiSeNet-03-分割常用损失函数(下)&分类器评价标准&摘要.vep [75.7M]
┃ ┃ ┣━━81.08BiSeNet-04-引言.vep [124.5M]
┃ ┃ ┣━━82.08BiSeNet-05-相关工作&算法架构总览.vep [83.4M]
┃ ┃ ┣━━83.08BiSeNet-06-算法结构详解&实验.vep [168.9M]
┃ ┃ ┣━━84.08BiSeNet-07-模型代码定义.vep [113M]
┃ ┃ ┣━━85.08BiSeNet-08-cityscapes数据集.vep [133.1M]
┃ ┃ ┣━━86.09DFANet-01-论文背景.vep [69.8M]
┃ ┃ ┣━━87.09DFANet-02-旷视软件部分补充..vep [100.6M]
┃ ┃ ┣━━88.09DFANet-03-旷视硬件部分补充..vep [65.9M]
┃ ┃ ┣━━89.09-DFANet-04-旷视官网.vep [114.6M]
┃ ┃ ┣━━90.09DFANet-05-引言.vep [157.1M]
┃ ┃ ┣━━91.09DFANet-06-相关工作_模型总览.vep [97.2M]
┃ ┃ ┣━━92.09DFANet-07-算法详解_实验分析..vep [215.9M]
┃ ┃ ┣━━93.09DFANet-08-代码定义(上)..vep [120.8M]
┃ ┃ ┣━━94.09DFANet-09-代码定义(下)..vep [73M]
┃ ┃ ┣━━95.10RedNet-01-深度图相关基本概念..vep [67.6M]
┃ ┃ ┣━━96.10RedNet-02-深度图相关研究方向..vep [68.5M]
┃ ┃ ┣━━97.10RedNet-03-引言.vep [80.3M]
┃ ┃ ┣━━98.10RedNet-04-相关工作&算法总览.vep [114M]
┃ ┃ ┣━━99.10RedNet-05-算法细节&实验..vep [156.1M]
┃ ┃ ┣━━100.10RedNet-06-模型搭建(上).vep [76.2M]
┃ ┃ ┣━━101.10RedNet-07-模型搭建(下).vep [183.9M]
┃ ┃ ┣━━102.10RedNet-08-NYUDv2数据集.vep [95.1M]
┃ ┃ ┣━━103.10RedNet-09-RGB-D分割代码.vep [117.4M]
┃ ┃ ┣━━104.11RDFNet-01-论文简介&特征融合.vep [109.2M]
┃ ┃ ┣━━105.11RDFNet-02-NYUDv2数据集.vep [95.9M]
┃ ┃ ┣━━106.11RDFNet-03-SUNRGBD数据集&摘要.vep [214.6M]
┃ ┃ ┣━━107.11RDFNet-04-RefineNet引言&相关工作.vep [260M]
┃ ┃ ┣━━108.11RDFNet-05-RefineNet相关背景.vep [130.9M]
┃ ┃ ┣━━109.11RDFNet-06-LW引言&相关工作&模型压缩.vep [242.9M]
┃ ┃ ┣━━110.11RDFNet-07-RDFNet引言&相关工作.vep [192M]
┃ ┃ ┣━━111.11RDFNet-08-RefineNet算法架构.vep [156.8M]
┃ ┃ ┣━━112.11RDFNet-09-LW&RDFNet算法架构.vep [380M]
┃ ┃ ┣━━113.11RDFNet-10-实验分析.vep [143.6M]
┃ ┃ ┣━━114.11RDFNet-11-总复习.vep [87.1M]
┃ ┃ ┣━━115.11RDFNet-12-RefineNet模型定义.vep.vep [169.8M]
┃ ┃ ┗━━116.11RDFNet-13-LW&RDF模型定义&SUNRGBD数据集.vep.vep [217.5M]
┃ ┣━━02.资料 [2.9G]
┃ ┃ ┣━━01-06代码+数据集
┃ ┃ ┣━━01FCN
┃ ┃ ┣━━02Unet-fusion
┃ ┃ ┣━━03SegNetDeconvNet
┃ ┃ ┣━━04deeplap
┃ ┃ ┣━━05GCN
┃ ┃ ┣━━06 DFN
┃ ┃ ┣━━07ENet
┃ ┃ ┣━━08BiSeNet
┃ ┃ ┣━━09DFANET
┃ ┃ ┣━━10-RedNet
┃ ┃ ┣━━11-RDFNet
┃ ┃ ┗━━Ubuntu系统安装教程.zip [2.9G]
┃ ┗━━03.答疑 [1.1G]
┃ ┣━━图像分割7.22直播答疑.vep [743.9M]
┃ ┗━━图像分割直播答疑.vep [373.2M]
┣━━3.目标检测 [28.3G]
┃ ┣━━1.视频 [15.7G]
┃ ┃ ┣━━1.目标检测开营直播.vep [379.2M]
┃ ┃ ┣━━2.基础知识-Dataloader和PascalVOC数据集讲解.vep.vep [86.8M]
┃ ┃ ┣━━3.01YOLO-01-发展历史和YOLO v1.vep.vep [111.1M]
┃ ┃ ┣━━4.01YOLO-02-YOLO v2.vep.vep [71.1M]
┃ ┃ ┣━━5.01YOLO-03-YOLO v3.vep.vep [75.9M]
┃ ┃ ┣━━6.01YOLO-04-代码复现.vep.vep [75.1M]
┃ ┃ ┣━━7.01YOLO-05-数据预处理和网络结构代码讲解.vep.vep [167.3M]
┃ ┃ ┣━━8.01YOLO-06-训练和检测代码讲解.vep.vep [48.2M]
┃ ┃ ┣━━9.02SSD-01-发展历史和论文泛读.vep.vep [44.5M]
┃ ┃ ┣━━10.02SSD-02-网络结构和具体算法.vep.vep [148.7M]
┃ ┃ ┣━━11.02SSD-03-代码复现.vep.vep [31.2M]
┃ ┃ ┣━━12.02SSD-04-代码讲解之数据处理.vep.vep [203M]
┃ ┃ ┣━━13.02SSD-05-代码讲解之训练过程.vep.vep [201.3M]
┃ ┃ ┣━━14.目标检测专题第一期答疑直播.vep [225.3M]
┃ ┃ ┣━━15.03FPN-01-FPN发展历史和论文导读.vep.vep [76.1M]
┃ ┃ ┣━━16.03FPN-02-FPN论文精读.vep.vep [123.2M]
┃ ┃ ┣━━17.03FPN-03-代码讲解.vep.vep [82.2M]
┃ ┃ ┣━━18.04RETINANET-01-发展历史和论文泛读1.vep.vep [60.4M]
┃ ┃ ┣━━19.04RETINANET-02-Focal Loss及网络结构2.vep.vep [72.5M]
┃ ┃ ┣━━20.04RETINANET-03-代码复现.vep.vep [22.5M]
┃ ┃ ┣━━21.04RETINANET-04-代码讲解之Dataloader.vep.vep [67M]
┃ ┃ ┣━━22.04RETINANET-05-代码讲解之RetinaNet网络结构.vep.vep [75.4M]
┃ ┃ ┣━━23.04RETINANET-06-代码讲解之Anchors和Focal Loss.vep.vep [119.3M]
┃ ┃ ┣━━24.04RETINANET-07-代码讲解之训练和测试过程.vep.vep [56.9M]
┃ ┃ ┣━━25.05FasterRCNN-01-目标检测基础知识.vep.vep [140.6M]
┃ ┃ ┣━━26.05FasterRCNN-02-研究背景&成果&意义.vep.vep [86.1M]
┃ ┃ ┣━━27.05FasterRCNN-03-论文网络结构&训练方法讲解.vep.vep [261.5M]
┃ ┃ ┣━━28.05FasterRCNN-04-实验结果及论文分析总结.vep.vep [37.4M]
┃ ┃ ┣━━29.05FasterRCNN-05-代码跑通讲解.vep.vep [115.5M]
┃ ┃ ┣━━30.05FasterRCNN-06-代码预览与数据预处理.vep.vep [99.9M]
┃ ┃ ┣━━31.05FasterRCNN-07-RPN和FasterRCNN代码讲解.vep.vep [93.2M]
┃ ┃ ┣━━32.05FasterRCNN-08-Proposal生成和网络训练代码讲解.vep.vep [134.1M]
┃ ┃ ┣━━33.06MaskRcnn-01-论文泛读1.vep.vep [132.2M]
┃ ┃ ┣━━34.06MaskRcnn-02-论文泛读2.vep.vep [226.4M]
┃ ┃ ┣━━35.06MaskRcnn精读-03-FasterRcnn回顾.vep.vep [98.6M]
┃ ┃ ┣━━36.06MaskRcnn精读-04-FPN.vep.vep [109.6M]
┃ ┃ ┣━━37.06MaskRcnn精读-05-RoiAlign.vep.vep [80.8M]
┃ ┃ ┣━━38.06MaskRcnn精读-06-实验分析.vep.vep [158.3M]
┃ ┃ ┣━━39.06MaskRcnn-07-代码01.vep.vep [343.8M]
┃ ┃ ┣━━40.06MaskRcnn-08-代码2.vep.vep [402M]
┃ ┃ ┣━━41.06MaskRcnn-09-代码3.vep.vep [415.3M]
┃ ┃ ┣━━42.07-01-Fcos论文泛读.vep.vep [171.3M]
┃ ┃ ┣━━43.07-02Fcos论文精读_FCN_YOLOV1回顾.vep.vep [82.4M]
┃ ┃ ┣━━44.07-03Fcos论文算法精读.vep.vep [301.6M]
┃ ┃ ┣━━45.07-04Fcos论文精读_损失函数.vep.vep [314.1M]
┃ ┃ ┣━━46.07-05Fcos论文精读_消融实验及论文总结.vep.vep [109.6M]
┃ ┃ ┣━━47.07-06Fcos代码_训练代码讲解.vep [185.6M]
┃ ┃ ┣━━48.07-07Fcos代码head结构.vep [157.6M]
┃ ┃ ┣━━49.07-08Fcos代码_Dataset讲解.vep [264.4M]
┃ ┃ ┣━━50.07-09Fcos代码_Backbone和网络结构.vep [336.6M]
┃ ┃ ┣━━51.07-10Fcos代码_loss和Inference讲解.vep [188.3M]
┃ ┃ ┣━━52.08EfficentDet-01-论文泛读.vep [202.4M]
┃ ┃ ┣━━53.08EfficientDet-02-精读_模型概要.vep [185.4M]
┃ ┃ ┣━━54.08EfficientDet-03-精读_Backbone网络.vep [183.3M]
┃ ┃ ┣━━55.08EfficientDet-04-精读_BiFPN模块.vep [448.1M]
┃ ┃ ┣━━56.08EfficientDet-05-精读_实验与消融实验.vep [501.4M]
┃ ┃ ┣━━57.08EfficientDet-06-代码讲解.vep [285.4M]
┃ ┃ ┣━━58.08EfficientDet-07-代码讲解_训练自己的数据集.vep [224.8M]
┃ ┃ ┣━━59.08EfficientDet-08-代码讲解_特征提取和特征融合.vep [280.8M]
┃ ┃ ┣━━60.09 cascade rcnn-09-结论和总结.vep [272.2M]
┃ ┃ ┣━━61.09cascade rcnn-01-论文泛读_结构介绍.vep [102M]
┃ ┃ ┣━━62.09cascade rcnn-02-论文泛读_摘要和总结.vep [232.4M]
┃ ┃ ┣━━63.09cascade rcnn-03 常见的评价指标_01.vep [188.3M]
┃ ┃ ┣━━64.09cascade rcnn-04-常见的评价指标_02.vep [159.2M]
┃ ┃ ┣━━65.09cascade rcnn-05-双阶段目标检测回顾.vep [137.4M]
┃ ┃ ┣━━66.09cascade rcnn-06-精读01.vep [536.9M]
┃ ┃ ┣━━67.09cascade rcnn-07-精读02.vep [525.1M]
┃ ┃ ┣━━68.09cascade rcnn-08-实验对比.vep [307.7M]
┃ ┃ ┣━━69.10CenterNet-01-论文泛读_背景介绍.vep [219.2M]
┃ ┃ ┣━━70.10CenterNet-02-论文泛读_摘要.vep [220.2M]
┃ ┃ ┣━━71.10CenterNet-03-论文精读_模型结构.vep [500.7M]
┃ ┃ ┣━━72.10CenterNet-04-论文精读_模型结构2.vep [596.8M]
┃ ┃ ┣━━73.10CenterNet-05-论文精读_实验设置.vep [551.4M]
┃ ┃ ┣━━74.10CenterNet-06-论文精读_实验结论和总结.vep [416.3M]
┃ ┃ ┣━━75.10CenterNet-07-代码讲解_训练数据和参数设置.vep [367.2M]
┃ ┃ ┣━━76.10CenterNet-08-代码讲解_网络主体结构.vep [337.7M]
┃ ┃ ┗━━77.10CenterNet-09-代码讲解_解码与预测.vep [403.3M]
┃ ┣━━2.资料 [12G]
┃ ┃ ┣━━01YOLO.zip [6G]
┃ ┃ ┣━━02 ssd.zip [48.3M]
┃ ┃ ┣━━03fpn.zip [34M]
┃ ┃ ┣━━04retinanet.zip [34.5M]
┃ ┃ ┣━━05Faster RCNN.zip [916.5M]
┃ ┃ ┣━━06mask rcnn.zip [63.8M]
┃ ┃ ┣━━07 FCOS.zip [446.2M]
┃ ┃ ┣━━08 EfficientDet.zip [1.1G]
┃ ┃ ┣━━09cascade rcnn.zip [852M]
┃ ┃ ┗━━10CenterNet.zip [2.6G]
┃ ┗━━3.答疑 [650.9M]
┃ ┗━━目标检测专题第一期答疑直播.vep [650.9M]
┣━━4.GAN [7.1G]
┃ ┣━━1.视频 [7.1G]
┃ ┃ ┣━━1.01GAN-01-论文摘要.vep [102.4M]
┃ ┃ ┣━━2.01GAN-02-论文背景.vep [45.9M]
┃ ┃ ┣━━3.01GAN-03-论文泛读.vep [131.2M]
┃ ┃ ┣━━4.01GAN-04-价值函数.vep [60.8M]
┃ ┃ ┣━━5.01GAN-05-训练流程&理论证明1.vep [55.5M]
┃ ┃ ┣━━6.01GAN-06-理论证明2&实验结果&总结展望.vep [78.1M]
┃ ┃ ┣━━7.01GAN-07-代码分析综述.vep [84.7M]
┃ ┃ ┣━━8.01GAN-08-代码分析精讲.vep [134.7M]
┃ ┃ ┣━━9.02CGAN-01-论文摘要&论文背景.vep [52.4M]
┃ ┃ ┣━━10.02CGAN-02-论文泛读.vep [58M]
┃ ┃ ┣━━11.02CGAN-03-论文精读1.vep [42.3M]
┃ ┃ ┣━━12.02CGAN-04-论文精读2.vep [78.4M]
┃ ┃ ┣━━13.02CGAN-05-代码讲解.vep [133.8M]
┃ ┃ ┣━━14.03DCGAN-01-论文摘要&论文背景..vep [62.4M]
┃ ┃ ┣━━15.03DCGAN-02-论文泛读.vep [100.1M]
┃ ┃ ┣━━16.03DCGAN-03-模型结构&图像生成..vep [84.6M]
┃ ┃ ┣━━17.03DCGAN-04-无监督表征学习&模型可视化&隐空间分析1..vep [86.5M]
┃ ┃ ┣━━18.03DCGAN-05-隐空间分析2&总结展望&论文总结.vep [70.8M]
┃ ┃ ┣━━19.03DCGAN-06-代码讲解1.vep [49.3M]
┃ ┃ ┣━━20.03DCGAN-07-代码讲解2.vep [120.3M]
┃ ┃ ┣━━21.04ITGAN-01-论文摘要&论文背景.vep [71.7M]
┃ ┃ ┣━━22.04ITGAN-02-论文泛读.vep [146.3M]
┃ ┃ ┣━━23.04ITGAN-03-GAN的训练改进.vep [99.4M]
┃ ┃ ┣━━24.04ITGAN-04-图像质量评价&半监督学习.vep [63.7M]
┃ ┃ ┣━━25.04ITGAN-05-实验结果&论文总结.vep [105.1M]
┃ ┃ ┣━━26.04ITGAN-06-代码讲解1.vep [93.4M]
┃ ┃ ┣━━27.04ITGAN-07-代码讲解2.vep [103.8M]
┃ ┃ ┣━━28.04ITGAN-08-代码讲解3.vep [131.8M]
┃ ┃ ┣━━29.05pix2pix-01-论文摘要&论文背景.vep [93.5M]
┃ ┃ ┣━━30.05pix2pix-02-论文成果及意义&论文泛读1.vep [74.8M]
┃ ┃ ┣━━31.05pix2pix-03-论文泛读2.vep [128.6M]
┃ ┃ ┣━━32.05pix2pix-04-目标函数&模型结构及训练参数.vep [93.2M]
┃ ┃ ┣━━33.05pix2pix-05-评价方式&目标函数分析&模型分析.vep [83.5M]
┃ ┃ ┣━━34.05pix2pix-06-应用分析&论文总结.vep [89.4M]
┃ ┃ ┣━━35.05pix2pix-07-代码讲解1.vep [114.3M]
┃ ┃ ┣━━36.05pix2pix-08-代码讲解2.vep [101.6M]
┃ ┃ ┣━━37.06cyclegan-01-论文摘要&研究背景.vep.vep [70.1M]
┃ ┃ ┣━━38.06cyclegan-02-论文成果及意义&论文泛读.vep.vep [249.7M]
┃ ┃ ┣━━39.06cyclegan-03-目标函数.vep.vep [85.6M]
┃ ┃ ┣━━40.06cyclegan-04-模型结构与训练参数&模型评价与比较&损失函数分析&图像重构质量.vep [137.3M]
┃ ┃ ┣━━41.06cyclegan-05-应用分析&论文总结.vep.vep [111M]
┃ ┃ ┣━━42.06cyclegan-06-代码讲解1.vep.vep [67M]
┃ ┃ ┣━━43.06cyclegan-07-代码讲解2.vep.vep [134.1M]
┃ ┃ ┣━━44.06cyclegan-08-代码讲解3.vep.vep [80.9M]
┃ ┃ ┣━━45.07ProGAN-01-论文摘要&研究背景.vep.vep [80.9M]
┃ ┃ ┣━━46.07ProGAN-02-论文成果及意义&论文泛读.vep.vep [120.2M]
┃ ┃ ┣━━47.07ProGAN-03-渐进式训练&Minibatch标准差.vep.vep [72.9M]
┃ ┃ ┣━━48.07ProGAN-04-归一化&评价指标&实验1.vep.vep [101.5M]
┃ ┃ ┣━━49.07ProGAN-05-实验2&论文总结.vep.vep [115.2M]
┃ ┃ ┣━━50.07ProGAN-06-代码讲解1.vep.vep [95.1M]
┃ ┃ ┣━━51.07ProGAN-07-代码讲解2.vep.vep [143.6M]
┃ ┃ ┣━━52.07ProGAN-08-代码讲解3.vep.vep [124.3M]
┃ ┃ ┣━━53.08StackGAN-01-论文摘要&研究背景.vep.vep [74.1M]
┃ ┃ ┣━━54.08StackGAN-02-论文成果及意义&论文泛读.vep.vep [95.3M]
┃ ┃ ┣━━55.08StackGAN-03-条件增强&两阶段的GAN1.vep.vep [58.7M]
┃ ┃ ┣━━56.08StackGAN-04-两阶段的GAN2&评价方式&性能比较.vep.vep [88.6M]
┃ ┃ ┣━━57.08StackGAN-05-组件分析&总结.vep.vep [116M]
┃ ┃ ┣━━58.08StackGAN-06-代码讲解1.vep.vep [62.1M]
┃ ┃ ┣━━59.08StackGAN-07-代码讲解2.vep.vep [140.1M]
┃ ┃ ┣━━60.08StackGAN-08-代码讲解3.vep.vep [84.4M]
┃ ┃ ┣━━61.09BigGAN-01-论文摘要&研究背景.vep.vep [90M]
┃ ┃ ┣━━62.09BigGAN-02-论文成果及意义&论文泛读.vep.vep [94.8M]
┃ ┃ ┣━━63.09BigGAN-03-大规模的GAN.vep.vep [91.5M]
┃ ┃ ┣━━64.09BigGAN-04-隐空间截断&不稳定性分析.vep.vep [128.3M]
┃ ┃ ┣━━65.09BigGAN-05-实验结果&论文总结.vep.vep [79.1M]
┃ ┃ ┣━━66.09BigGAN-06-代码讲解1.vep.vep [93.5M]
┃ ┃ ┣━━67.09BigGAN-07-代码讲解2.vep.vep [160.3M]
┃ ┃ ┣━━68.10StyleGAN-01-论文摘要&研究背景.vep.vep [69.3M]
┃ ┃ ┣━━69.10StyleGAN-02-论文成果及意义&论文泛读.vep.vep [111.6M]
┃ ┃ ┣━━70.10StyleGAN-03-基于样式的生成器架构.vep.vep [58.9M]
┃ ┃ ┣━━71.10StyleGAN-04-实验结果&生成器的属性分析.vep.vep [107.4M]
┃ ┃ ┣━━72.10StyleGAN-05-隐变量解耦1.vep.vep [68.1M]
┃ ┃ ┣━━73.10StyleGAN-06-隐变量解耦2&论文总结.vep.vep [83.7M]
┃ ┃ ┣━━74.10StyleGAN-07-代码讲解1.vep.vep [75.4M]
┃ ┃ ┣━━75.10StyleGAN-08-代码讲解2.vep.vep [133.4M]
┃ ┃ ┗━━76.10StyleGAN-09-代码讲解3.vep.vep [75M]
┃ ┗━━2.资料 [0B]
┃ ┣━━01
┃ ┣━━02
┃ ┣━━03
┃ ┣━━04
┃ ┣━━05
┃ ┣━━06
┃ ┣━━07
┃ ┣━━08
┃ ┣━━09
┃ ┣━━10
┃ ┗━━直播课件
┣━━5.OCR [23.9G]
┃ ┣━━01.视频 [23.7G]
┃ ┃ ┣━━1.CRNN1-泛读-背景论文.vep.vep [357.8M]
┃ ┃ ┣━━2.CRNN2-泛读-研究成果及意义.vep.vep [103.7M]
┃ ┃ ┣━━3.CRNN3-泛读-LSTM、CTC、Beam Search、论文泛读.vep.vep [230.6M]
┃ ┃ ┣━━4.CRNN4-精读-原有模型.vep.vep [62.4M]
┃ ┃ ┣━━5.CRNN5-精读-CRNN网络结构、论文细节一.vep.vep [82.8M]
┃ ┃ ┣━━6.CRNN6-精读-论文细节二三四.vep.vep [194.2M]
┃ ┃ ┣━━7.CRNN7-精读-实验结果及总结.vep.vep [54.9M]
┃ ┃ ┣━━8.crnn-code-1.vep.vep [198.5M]
┃ ┃ ┣━━9.crnn-code-2.vep.vep [209.2M]
┃ ┃ ┣━━10.crnn-code-3.vep.vep [171.1M]
┃ ┃ ┣━━11.crnn-code-4.vep.vep [44M]
┃ ┃ ┣━━12.crnn-code-5.vep.vep [45.9M]
┃ ┃ ┣━━13.2.1 attention_OCR-研究背景、成果、意义.vep [137M]
┃ ┃ ┣━━14.2.10 attention_OCR-代码-数据集.vep [195.4M]
┃ ┃ ┣━━15.2.11 attention_OCR-model-1.vep [185.7M]
┃ ┃ ┣━━16.2.12 attention_OCR-model-2.vep [75.7M]
┃ ┃ ┣━━17.2.13 attention_OCR-model-3.vep [82M]
┃ ┃ ┣━━18.2.14 attention_OCR-model-4.vep [127.2M]
┃ ┃ ┣━━19.2.15 attention_OCR-model-5.vep [242.7M]
┃ ┃ ┣━━20.2.16 attention_OCR-model-6.vep [46.5M]
┃ ┃ ┣━━21.2.17 attention_OCR-train.vep [153.7M]
┃ ┃ ┣━━22.2.18 总结-CRNN回顾.vep [164.2M]
┃ ┃ ┣━━23.2.19 总结-Attention-based-回顾及对比.vep [274.5M]
┃ ┃ ┣━━24.2.2 attention_OCR-论文知识点讲解.vep [218.2M]
┃ ┃ ┣━━25.2.3 attention_OCR-精读-论文总览及模型细节一.vep [126.5M]
┃ ┃ ┣━━26.2.4 attention_OCR-精读-模型细节二.vep [206.1M]
┃ ┃ ┣━━27.2.5 attention_OCR-精读-模型细节三.vep [55.1M]
┃ ┃ ┣━━28.2.6 attention_OCR-精读-模型细节四.vep [18.5M]
┃ ┃ ┣━━29.2.7 attention_OCR-精读-论文中的细节描述.vep [164.7M]
┃ ┃ ┣━━30.2.8 attention_OCR-精读-实验.vep [65.9M]
┃ ┃ ┣━━31.2.9 attention_OCR-精读-总结.vep [25.1M]
┃ ┃ ┣━━32.3.01 CTPN-论文讲解.vep [132.2M]
┃ ┃ ┣━━33.3.02 CTPN-论文详解.vep [117M]
┃ ┃ ┣━━34.3.03 CTPN-论文详解.vep [194.5M]
┃ ┃ ┣━━35.3.04 CTPN-论文详解.vep [616.1M]
┃ ┃ ┣━━36.3.05 CTPN-代码详解.vep [353M]
┃ ┃ ┣━━37.3.06 CTPN-代码详解.vep [592.8M]
┃ ┃ ┣━━38.3.07 CTPN代码详解.vep [421.1M]
┃ ┃ ┣━━39.3.08 CTPN代码详解.vep [645.7M]
┃ ┃ ┣━━40.4.01 EAST_1.vep [99.9M]
┃ ┃ ┣━━41.4.02 EAST_2.vep [336M]
┃ ┃ ┣━━42.4.03 EAST_3.vep [153.9M]
┃ ┃ ┣━━43.4.04 EAST_4.vep [436.6M]
┃ ┃ ┣━━44.4.05 EAST_code_0.vep [158.6M]
┃ ┃ ┣━━45.4.06 EAST_code_1.vep [527.3M]
┃ ┃ ┣━━46.4.07 EAST_code_2.vep [678M]
┃ ┃ ┣━━47.4.08 EAST_code_3.vep [573.6M]
┃ ┃ ┣━━48.4.09EAST_code_4.vep [278.1M]
┃ ┃ ┣━━49.4.10 EAST_code_5.vep [765M]
┃ ┃ ┣━━50.5.01 Adv_EAST.vep [102.6M]
┃ ┃ ┣━━51.5.02 AdvEAST_code_1.vep [654.3M]
┃ ┃ ┣━━52.5.03 Adv_EAST_code_2.vep [430.1M]
┃ ┃ ┣━━53.5.04 Adv_EAST_code_3.vep [425.7M]
┃ ┃ ┣━━54.6.01 PSE_1.vep [199.8M]
┃ ┃ ┣━━55.6.02 PSE_2.vep [221.1M]
┃ ┃ ┣━━56.6.03 PSE_3.vep [359M]
┃ ┃ ┣━━57.6.04 PSE_4.vep [135.2M]
┃ ┃ ┣━━58.6.05 PSE_code_0.vep [195.5M]
┃ ┃ ┣━━59.6.06PSE_code_1.vep [361M]
┃ ┃ ┣━━60.6.07 PSE_code_2.vep [632.3M]
┃ ┃ ┣━━61.6.08 PSE_code_3.vep [337.5M]
┃ ┃ ┣━━62.6.09 PSE_code_4.vep [412.7M]
┃ ┃ ┣━━63.7.01 PAN_1.vep [125.5M]
┃ ┃ ┣━━64.7.02 PAN_2.vep [93.6M]
┃ ┃ ┣━━65.7.03 PAN_3.vep [157.5M]
┃ ┃ ┣━━66.7.04 PAN_4.vep [377.2M]
┃ ┃ ┣━━67.7.05 PAN_5.vep [154.6M]
┃ ┃ ┣━━68.7.06 PAN_code_1.vep [529.7M]
┃ ┃ ┣━━69.7.07 PAN_code_2.vep [694.3M]
┃ ┃ ┣━━70.7.08 PAN_code_3.vep [495.7M]
┃ ┃ ┣━━71.7.09 PAN_code_4.vep [257.7M]
┃ ┃ ┣━━72.8.01 DB_1.vep [117.4M]
┃ ┃ ┣━━73.8.02 DB_2.vep [145.8M]
┃ ┃ ┣━━74.8.03 DB_3.vep [131.5M]
┃ ┃ ┣━━75.8.04 DB_4.vep [295.9M]
┃ ┃ ┣━━76.8.05 DB_5.vep [113.8M]
┃ ┃ ┣━━77.8.06 DB_code_0.vep [373.6M]
┃ ┃ ┣━━78.8.07 DB_code_1.vep [593.3M]
┃ ┃ ┣━━79.9.01 ASTER_1.vep [132.7M]
┃ ┃ ┣━━80.9.02 ASTER_2.vep [110.2M]
┃ ┃ ┣━━81.9.03 ASTER_3.vep [259.1M]
┃ ┃ ┣━━82.9.04 ASTER_4.vep [375.4M]
┃ ┃ ┣━━83.9.05 ASTER_5.vep [64.2M]
┃ ┃ ┣━━84.9.06 ASTER_code_0.vep [224.9M]
┃ ┃ ┣━━85.9.07 ASTER_code_1.vep [455M]
┃ ┃ ┣━━86.9.08 ASTER_code_2.vep [665.4M]
┃ ┃ ┣━━87.9.09 ASTER_code_3.vep [455.4M]
┃ ┃ ┣━━88.9.10 ASTER_code_4.vep [435.9M]
┃ ┃ ┗━━89.9.11 ASTER_code_5.vep [594.5M]
┃ ┗━━02.资料 [165.4M]
┃ ┣━━02
┃ ┣━━03 CTPN
┃ ┣━━04-05 EAST
┃ ┣━━06 PSENet
┃ ┣━━07 PAN
┃ ┣━━08 DB
┃ ┣━━09 ASTER
┃ ┗━━01 CRNN.zip [165.4M]
┣━━6.轻量化网络 [8.1G]
┃ ┣━━01.视频 [8.1G]
┃ ┃ ┣━━1.01mobilenet-01-背景介绍.vep [51.8M]
┃ ┃ ┣━━2.01mobilenet-02-论文结构&摘要精读.vep [143.8M]
┃ ┃ ┣━━3.01mobilenet-03-主体架构&深度可分离卷积.vep [114.1M]
┃ ┃ ┣━━4.01MobileNet-04-超参数.vep [82.4M]
┃ ┃ ┣━━5.01mobilenet-05-后续创新及改进.vep [119.4M]
┃ ┃ ┣━━6.01MobileNets-06-代码结构.vep [310.5M]
┃ ┃ ┣━━7.01MobileNets-07-模型设计.vep [110.9M]
┃ ┃ ┣━━8.01MobileNets-08-模型评估.vep [85.6M]
┃ ┃ ┣━━9.02shufflenet-01-研究背景&意义.vep [62M]
┃ ┃ ┣━━10.02shufflenet-02-论文结构&摘要.vep [155.3M]
┃ ┃ ┣━━11.02shufflenet-03-分组点卷积.vep [263.9M]
┃ ┃ ┣━━12.02shufflenet-04-通道重排.vep [338.5M]
┃ ┃ ┣━━13.02shufflenet-05-总结&创新.vep [189.6M]
┃ ┃ ┣━━14.02shufflenet-06-复现网络结构.vep [116M]
┃ ┃ ┣━━15.02shufflenet-07-数据预处理.vep [372.5M]
┃ ┃ ┣━━16.02shufflenet-08-模型设计.vep [499.6M]
┃ ┃ ┣━━17.02shufflenet-09-模型评估.vep [241.8M]
┃ ┃ ┣━━18.03squeezenet-01-研究背景&成果&意义.vep [148.1M]
┃ ┃ ┣━━19.3squeezenet-02-结构&泛读.vep [216.7M]
┃ ┃ ┣━━20.03squeezenet-03-cnn结构设计策略&Fire Module内部.vep [303.1M]
┃ ┃ ┣━━21.03squeezenet-04-网络架构及细节&试验结果及分析.vep [394.6M]
┃ ┃ ┣━━22.03squeezenet-05-模型预处理、加载.vep [456.4M]
┃ ┃ ┣━━23.03squeezenet-06-模型结构构造.vep [257.4M]
┃ ┃ ┣━━24.03squeezenet-07-模型评估.vep [300.9M]
┃ ┃ ┣━━25.04xception-01-研究背景&成果&泛读.vep [86.7M]
┃ ┃ ┣━━26.04xception-02-网络发展.vep [36.9M]
┃ ┃ ┣━━27.04xception-03-网络结构&深度可分离卷积对比.vep [73.6M]
┃ ┃ ┣━━28.04xception-04-实验结果及论文分析&论文总结.vep [25.8M]
┃ ┃ ┣━━29.04xception-05-准备工作.vep [122.2M]
┃ ┃ ┣━━30.04xception-06-模型设计.vep [62M]
┃ ┃ ┣━━31.04xception-07-模型训练及评估.vep [55.1M]
┃ ┃ ┣━━32.05 knowledge distillation-01-论文泛读.vep [92.8M]
┃ ┃ ┣━━33.05 knowledge distillation-02-集成模型思想.vep [24.9M]
┃ ┃ ┣━━34.05 knowledge distillation-03-知识蒸馏思想和方法.vep [78.8M]
┃ ┃ ┣━━35.05 knowledge distillation-04-专家集成模型及知识蒸馏实验.vep [31.7M]
┃ ┃ ┣━━36.05knowledge distillation-05-项目代码总览与小结.vep [75.5M]
┃ ┃ ┣━━37.05knowledge distillation-06-教师网络与学生网络的构建.vep [66.6M]
┃ ┃ ┣━━38.05knowledge distillation-07-教师网络与学生网络的训练.vep [65.1M]
┃ ┃ ┣━━39.05knowledge distillation-08-知识蒸馏训练学生网络.vep [57.4M]
┃ ┃ ┣━━40.06attention-transfer-01-研究背景&成果&摘要.vep [75.1M]
┃ ┃ ┣━━41.06attention-transfer-02-计算机视觉中的注意力转移.vep [81.5M]
┃ ┃ ┣━━42.06attention-transfer-03-基于激活&梯度&的注意力图&实验.vep [70.1M]
┃ ┃ ┣━━43.06attention-transfer-04-搭建训练教师模型&学生模型.vep [102.7M]
┃ ┃ ┣━━44.06attention-transfer-05-实现基于激活&梯度注意力图&训练学生.vep [191.9M]
┃ ┃ ┣━━45.07-研究背景&成果&摘要.01.vep [91.8M]
┃ ┃ ┣━━46.07-计算网络参数量计算量-02.vep [58.4M]
┃ ┃ ┣━━47.07-剪枝介绍03.vep [77M]
┃ ┃ ┣━━48.07-迭代式剪枝.04.vep [36.7M]
┃ ┃ ┣━━49.07-搭建并训练目标网络.05.vep [93M]
┃ ┃ ┣━━50.07-非结构化剪枝&结构化剪枝&可视化.06.vep [97.3M]
┃ ┃ ┣━━51.08Network Slimming-01-研究背景、成果、意义及论文泛读.vep [82.5M]
┃ ┃ ┣━━52.08Network Slimming-02-CNN通道剪枝、Batch Norm.vep [74.1M]
┃ ┃ ┣━━53.08Network Slimming-03-通道剪枝方法、结果及分析、总结.vep [80.6M]
┃ ┃ ┣━━54.08Network Slimming-04-搭建并训练目标网络.vep.vep [138.5M]
┃ ┃ ┣━━55.08Network Slimming-05-用bn层剪枝&结构分析.vep.vep [100.3M]
┃ ┃ ┣━━56.09Pruning for Efficient Inference-01–研究背景、成果.vep [104.2M]
┃ ┃ ┣━━57.09Pruning for Efficient Inference-02-通道重要性判断.vep [89.5M]
┃ ┃ ┣━━58.09Pruning for Efficient Inference-03-FLOPs正则化.vep [68.2M]
┃ ┃ ┣━━59.09pruning-04-目标网络搭建.vep.vep [116M]
┃ ┃ ┣━━60.09pruning-05-Hook&FLOPs.vep.vep [45M]
┃ ┃ ┗━━61.09pruning-06-迭代式泰勒剪枝过程.vep.vep [137.7M]
┃ ┗━━02.资料 [0B]
┃ ┣━━01MobileNets
┃ ┣━━02Shufflenet
┃ ┣━━03Squeezenet
┃ ┣━━04Xception
┃ ┣━━05KD
┃ ┣━━06attention-transfer
┃ ┣━━07Learning-both-weights-and-connections
┃ ┣━━08network-slimming
┃ ┗━━09PRUNING CONVOLUTIONAL NEURAL NETWORKS
┣━━7.CV-Transformer [15.1G]
┃ ┣━━01.视频 [13.4G]
┃ ┃ ┣━━【6月27日】CV-transformer VIT代码详解.vep [1G]
┃ ┃ ┣━━【7月11日】CV-transformer Swin Transformer代码详解.vep [1.3G]
┃ ┃ ┣━━【7月15日】CV-transformer DETR 论文泛读.vep [994.6M]
┃ ┃ ┣━━【7月18日】CV-transformer DETR代码讲解.vep [1.3G]
┃ ┃ ┣━━【7月1日】CV-transformer PVT论文详解.vep [1.1G]
┃ ┃ ┣━━【7月22日】CV-transformer Deformable DETR论文详解.vep [1.1G]
┃ ┃ ┣━━【7月25日】CV-transformer Deformable DETR代码详解.vep [1.1G]
┃ ┃ ┣━━【7月29日】CV-transformer Sparse R-CNN论文详解.vep [980.4M]
┃ ┃ ┣━━【7月4日】CV-transformer PVT代码详解.vep [1.1G]
┃ ┃ ┣━━【7月8日】CV-transformer Swin Transformer论文详解.vep [1.1G]
┃ ┃ ┣━━【8月1日】CV-transformer Sparse R-CNN代码详解.vep [1.1G]
┃ ┃ ┣━━6-16 CV transformer 体验课直播回放.vep [284.9M]
┃ ┃ ┣━━6-17 CV-transformer VIT论文讲解直播回放.vep [538.4M]
┃ ┃ ┗━━6-25 CV-transformer VIT论文讲解直播回放.vep [566.8M]
┃ ┗━━00.资料.zip [1.7G]
┗━━前沿直播 [11.2G]
┣━━01.视频 [10.6G]
┃ ┣━━01-第一场直播：StyleGAN2.vep [1.2G]
┃ ┣━━02-第二场直播—自监督.vep [440.1M]
┃ ┣━━03-第三场—YOLO4直播.vep [447.2M]
┃ ┣━━04-第四场.vep [1.4G]
┃ ┣━━05-第五场-M2Det.vep [861.7M]
┃ ┣━━第八场直播——行人检测.vep [479.5M]
┃ ┣━━第九场直播——Fast SCNN.vep [683.4M]
┃ ┣━━第六场直播——车道线检测.vep [488.4M]
┃ ┣━━第七次直播——清华本硕学长论文分享.vep [285.8M]
┃ ┣━━第十场直播：人体姿态估计.vep [499.3M]
┃ ┣━━第十二场直播——异常检测.vep [242.4M]
┃ ┣━━第十六场直播——顶刊审稿人教你发稿小tips.vep [1.6G]
┃ ┣━━第十三场直播——如何快速发论文.vep [440.8M]
┃ ┣━━第十四场直播——漫谈CV Transformer.vep [711.4M]
┃ ┣━━第十五场直播——医学分割.vep [461.4M]
┃ ┗━━第十一场直播：如何做科研.vep [501.1M]
┗━━00.资料.zip [583.9M]

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