Basic
One-Stage-Detector와 Two-Stage-Detector
[Posting]
Fine Tuning
[Posting]
Network
Gradient-Based Learning Applied to Document Recognition (LeNet)
[Paper] [Posting] [Pytorch]
ImageNet Classification with Deep Convolutional Neural Networks (AlexNet)
[Paper] [Posting] [Pytorch]
Very Deep Convolutional Networks for Large-Scale Image Recognition (VGG)
[paper] [Posting] [Pytorch]
Going Deeper with Convolutions (GoogleNet)
[paper] [Posting] [Pytorch]
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition (Sppnet)
[paper] [Posting] [Pytorch]
Deep Residual Learning for Image Recognition (ResNet-50)
[paper] [Posting] [Pytorch]
Xception : Deep Learning with Depthwise Separable Convolutions (Xception)
[paper] [Posting] [Pytorch]
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications (MobileNet)
[paper] [Posting] [Pytorch]
Densely Connected Convolutional Networks (DenseNet)
[paper] [Posting] [Pytorch]
Squeeze-and-Excitation Networks (SeNet)
[paper] [Posting] [Pytorch]
Object Detection
Rich feature hierarchies for accurate object detection and semantic segmentation (R-CNN)
[Paper] [Posting] [Pytorch]
OverFeat : Integrated Recognition, Localization and Detection using Convolutional Networks
[paper] [Posting] [Pytorch]
Fast R-CNN
[paper] [Posting] [Pytorch]
Faster R-CNN
[paper] [Posting] [Pytorch]
OHEM
[paper] [Posting] [Pytorch]
YOLO v1
[paper] [Posting] [Pytorch]
SSD
[paper] [Posting] [Pytorch]
R-FCN
[paper] [Posting] [Pytorch]
YOLO v2
[paper] [Posting] [Pytorch]
FPN
[paper] [Posting] [Pytorch]
Retina Net
[paper] [Posting] [Pytorch]
Mask R-CNN
[paper] [Posting] [Pytorch]
YOLO v3
[paper] [Posting] [Pytorch]
RefineDet
[paper] [Posting] [Pytorch]
M2Det
[paper] [Posting] [Pytorch]