在 ImageNet 上表现出色的经典模型

ImageNet 是由李飞飞主导建立的一个超大的计算机视觉数据集。基于此数据集，自 2010 年至 2017 年举办 ImageNet 挑战赛，即 ImageNet Large Scale Visual Recognition Challenge (ILSVRC)。这篇文章以时间顺序记录了在 ImageNet 上表现出色的模型，很多也是 ILSVRC 上的冠军。

预训练模型使用方法

TensorFlow

• https://www.tensorflow.org/tutorials/images/transfer_learning
• https://keras.io/api/applications/

PyTorch

• https://pytorch.org/vision/stable/models.html
• https://github.com/rwightman/pytorch-image-models
• https://pytorch.org/hub
• https://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html

模型论文

参考链接：https://paperswithcode.com/sota/image-classification-on-imagenet

VGG

Very Deep Convolutional Networks for Large-Scale Image Recognition
https://arxiv.org/abs/1409.1556
Submitted on 4 Sep 2014

ResNet

Deep Residual Learning for Image Recognition
https://arxiv.org/abs/1512.03385
Submitted on 10 Dec 2015

InceptionV3

Rethinking the Inception Architecture for Computer Vision
https://arxiv.org/abs/1512.00567
Submitted on 2 Dec 2015

InceptionResNetV2

Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
https://arxiv.org/abs/1602.07261
Submitted on 23 Feb 2016

DenseNet

Densely Connected Convolutional Networks
https://arxiv.org/abs/1608.06993
Submitted on 25 Aug 2016

Xception

Xception: Deep Learning with Depthwise Separable Convolutions
https://arxiv.org/abs/1610.02357
Submitted on 7 Oct 2016

NASNet

Neural Architecture Search with Reinforcement Learning
https://arxiv.org/abs/1611.01578
Submitted on 5 Nov 2016

EfficientNet

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://arxiv.org/abs/1905.11946
Submitted on 28 May 2019