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：
文章2：
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 | 语义分割 | 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 | 语义分割 | DeepLab | GitHub - fregu856/deeplabv3: PyTorch implementation of DeepLabV3, trained on the Cityscapes dataset. |
| 4 | 语义分割 | PSPNet | GitHub - Lextal/pspnet-pytorch: PyTorch implementation of PSPNet segmentation network |
| 5 | 语义分割 | SegNet | GitHub - preddy5/segnet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation |
| 6 | 语义分割 | 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 | 实例分割 | PANet | https://github.com/kaixin96/PANet |
| 9 | 实例分割 | YOLACT | https://github.com/dbolya/yolact |
| 10 | 实例分割 | SOLO | https://github.com/iambankaratharva/SOLO-Instance-Segmentation |
| 11 | 实例分割 | 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 | 人脸 | MTCNN | GitHub - ipazc/mtcnn: MTCNN face detection implementation for TensorFlow, as a PIP package. |
| 3 | 人脸 | FaceBoxes | GitHub - zisianw/FaceBoxes.PyTorch: A PyTorch Implementation of FaceBoxes |
| 4 | 人脸 | 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 | 人体 | HRNet | https://github.com/HRNet/HigherHRNet-Human-Pose-Estimation |
| 7 | 人体 | CPM | GitHub - PanZiqiAI/CPM-Clothes-Keypoints-Detection: Convolutional Pose Machine implemented for clothes key points detection. |
| 8 | 人体 | 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 | 人体 | AlphaPose | GitHub - Amanbhandula/AlphaPose: AlphaPose Implementation in Pytorch along with the pre-trained weights |
| 10 | 人体 | 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。