- 目标检测--Focal Loss for Dense Object Detection
- 视频目标检测--Flow-Guided Feature Aggregation for Video Object Detection
- 视频检测分割--Deep Feature Flow for Video Recognition
- 有方向的CNN--Oriented Response Networks
- 语义分割--Efficient and Robust Deep Networks for Semantic Segmentation
- 语义分割--Efficient Deep Models for Monocular Road Segmentation
- CNN光流计算2
- CNN光流计算--FlowNet: Learning Optical Flow with Convolutional Networks
- 2.2Virtualbox高级应用构建本地大数据集群服务器
- caffe 的命令行训练与测试
- 人脸对齐--Robust face landmark estimation under occlusion
- 分布式服务架构：原理、设计与实战打卡记录(二)
- 1.2 linux使用技巧快速入门
- 人脸对齐--Face Alignment by Explicit Shape Regression
- 1.1 Virtualbox虚拟机快速入门
- 人脸对齐--Boosted Regression Active Shape Models
- 车辆检测--A Closer Look at Faster R-CNN for Vehicle Detection
- 2.1 TensorFlow模型的理解
- caffe学习笔记2-caffe命令行训练与测试
- R语言︱缺失值处理之多重插补——mice包
腾讯云开发者
