计算机视觉四大任务模型汇总

计算机视觉中有四大核心任务：

      1-分类任务、2-目标检测任务、3-目标分割任务 和 4-关键点检测任务

文章1：

一文读懂计算机视觉4大任务

文章2：

图像的目标分割任务：语义分割和实例分割

 不同任务之间相关但不完全相同，因此不同的任务最好选择相应的模型，话不多说，看表：

（注：表中github链接并不一定是模型的正式版本，只是本文用于展示模型的网络结构和应用）

1-分类任务模型

序号	模型	ipynb模型的github链接
1	LeNet	https://github.com/udacity/CarND-LeNet-Lab
2	AlexNet	https://github.com/Fannjh/AlexNet-TF
3	VGGNet	https://github.com/Fozan-Talat/Image-Classifier-VGG
4	GoogLeNet	GitHub - AbdelrahmanShehata482/CNN-project: CNN_Project (py and ipynb code ) (Vgg16-GoogleNet from scratch)
5	ResNet	GitHub - ry/tensorflow-resnet: ResNet model in TensorFlow
6	DenseNet	GitHub - titu1994/DenseNet: DenseNet implementation in Keras
7	MobileNet	https://github.com/Zehaos/MobileNet
8	EfficientNet	https://github.com/qubvel/efficientnet
9	SVM(支持向量机)	https://github.com/Think103/-

2-目标检测任务模型

序号	模型	ipynb模型的github链接
1	R-CNN（已过时）
2	Fast R-CNN（已过时）
3	Faster R-CNN	GitHub - kbardool/Keras-frcnn: Keras Implementation of Faster R-CNN
4	YOLO	https://github.com/ultralytics/yolov5
5	SSD	https://github.com/lufficc/SSD
6	RetinaNet	https://github.com/fizyr/keras-retinanet
7	Mask R-CNN	https://github.com/SanmathiK/PedNet
8	EfficientDet	GitHub - xuannianz/EfficientDet: EfficientDet (Scalable and Efficient Object Detection) implementation in Keras and Tensorflow
9	CenterNet	https://github.com/xingyizhou/CenterNet

3-目标分割任务模型

序号	分割类型	模型	ipynb模型的github链接
1	语义分割	FCN	GitHub - wkentaro/pytorch-fcn: PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
2		U-Net	GitHub - yingkaisha/keras-unet-collection: The Tensorflow, Keras implementation of U-net, V-net, U-net++, UNET 3+, Attention U-net, R2U-net, ResUnet-a, U^2-Net, TransUNET, and Swin-UNET with optional ImageNet-trained backbones.
3		DeepLab	GitHub - fregu856/deeplabv3: PyTorch implementation of DeepLabV3, trained on the Cityscapes dataset.
4		PSPNet	GitHub - Lextal/pspnet-pytorch: PyTorch implementation of PSPNet segmentation network
5		SegNet	GitHub - preddy5/segnet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
6		HRNet	GitHub - HRNet/HRNet-Image-Classification: Train the HRNet model on ImageNet
7	实例分割	Mask R-CNN	https://github.com/saikoneru/Instance-Segementation
8		PANet	https://github.com/kaixin96/PANet
9		YOLACT	https://github.com/dbolya/yolact
10		SOLO	https://github.com/iambankaratharva/SOLO-Instance-Segmentation
11		PointRend	https://github.com/zsef123/PointRend-PyTorch

4-关键点检测任务模型

序号	检测目标	模型	ipynb模型的github链接
1	人脸	Dlib	GitHub - davisking/dlib: A toolkit for making real world machine learning and data analysis applications in C++
2		MTCNN	GitHub - ipazc/mtcnn: MTCNN face detection implementation for TensorFlow, as a PIP package.
3		FaceBoxes	GitHub - zisianw/FaceBoxes.PyTorch: A PyTorch Implementation of FaceBoxes
4		PRNet	GitHub - yfeng95/PRNet: Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network (ECCV 2018)
5	人体	OpenPose	GitHub - Hzzone/pytorch-openpose: pytorch implementation of openpose including Hand and Body Pose Estimation.
6		HRNet	https://github.com/HRNet/HigherHRNet-Human-Pose-Estimation
7		CPM	GitHub - PanZiqiAI/CPM-Clothes-Keypoints-Detection: Convolutional Pose Machine implemented for clothes key points detection.
8		Mask R-CNN with Keypoint Detection Branch	GitHub - chrispolo/Keypoints-of-humanpose-with-Mask-R-CNN: Use the Mask RCNN for the human pose estimation
9		AlphaPose	GitHub - Amanbhandula/AlphaPose: AlphaPose Implementation in Pytorch along with the pre-trained weights
10		MoveNet	GitHub - fire717/movenet.pytorch: A Pytorch implementation of MoveNet from Google. Include training code and pre-trained model.

需要说明，上表中模型名称并不单指某个模型，而是一类模型统称，如YOLO模型实际包括了yolov1~yolov10的10个系列。