【计算机视觉 | SOTA模型】整理了197个经典SOTA模型，涵盖图像分类、目标检测等方向_图片分类sota

一、图像分类SOTA模型（15个）

1.模型：AlexNet
论文题目：Imagenet Classification with Deep Convolution Neural Network

2.模型：VGG
论文题目：Very Deep Convolutional Networks for Large-Scale Image Recognition

3.模型：GoogleNet
论文题目：Going Deeper with Convolutions

4.模型：ResNet
论文题目：Deep Residual Learning for Image Recognition

5.模型：ResNeXt
论文题目：Aggregated Residual Transformations for Deep Neural Networks

6.模型：DenseNet
论文题目：Densely Connected Convolutional Networks

7.模型：MobileNet
论文题目：MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

8.模型：SENet
论文题目：Squeeze-and-Excitation Networks

9.模型：DPN
论文题目：Dual Path Networks

10.模型：IGC V1
论文题目：Interleaved Group Convolutions for Deep Neural Networks

11.模型：Residual Attention Network
论文题目：Residual Attention Network for Image Classification

12.模型：ShuffleNet
论文题目：ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

13.模型：MnasNet
论文题目：MnasNet: Platform-Aware Neural Architecture Search for Mobile

14.模型：EfficientNet
论文题目：EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

15.模型：NFNet
论文题目：MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applic

二、图像生成SOTA模型（16个）

Progressive Growing of GANs for Improved Quality, Stability, and Variation
1

A Style-Based Generator Architecture for Generative Adversarial Networks
1

Analyzing and Improving the Image Quality of StyleGAN
1

Alias-Free Generative Adversarial Networks
1

Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images
1

A Contrastive Learning Approach for Training Variational Autoencoder Priors
1

StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets
1

Diffusion-GAN: Training GANs with Diffusion
1

Improved Training of Wasserstein GANs
1

Self-Attention Generative Adversarial Networks
1

Large Scale GAN Training for High Fidelity Natural Image Synthesis
1

CSGAN: Cyclic-Synthesized Generative Adversarial Networks for Image-to-Image Transformation
1

LOGAN: Latent Optimisation for Generative Adversarial Networks
1

A U-Net Based Discriminator for Generative Adversarial Networks
1

Instance-Conditioned GAN
1

Conditional GANs with Auxiliary Discriminative Classifier
1

三、目标检测SOTA模型（16个）

Rich feature hierarchies for accurate object detection and semantic segmentation
1

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
1

Fast R-CNN
1

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
1

Training Region-based Object Detectors with Online Hard Example Mining
1

R-FCN: Object Detection via Region-based Fully Convolutional Networks
1

Mask R-CNN
1

You Only Look Once: Unified, Real-Time Object Detection
1

SSD: Single Shot Multibox Detector
1

Feature Pyramid Networks for Object Detection
1

Focal Loss for Dense Object Detection
1

Accurate Single Stage Detector Using Recurrent Rolling Convolution
1

CornerNet: Detecting Objects as Paired Keypoints
1

M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network
1

Fully Convolutional One-Stage Object Detection
1

ObjectBox: From Centers to Boxes for Anchor-Free Object Detection
1