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入门cv必读的10篇baseline论文
2022-08-09 06:54:00 【just do it now】
1. NIPS-2012，Alexnet：深度学习CV领域划时代论文，具有里程碑意义
《ImageNet Classification with Deep Convolutional Neural Networks》
2. ICLR-2015，VGG net：开启3*3卷积堆叠时代
《Very Deep Convolutional Networks for Large-Scale Image Recognition》
3. CVPR-2015，googlenet v1:Google系列论文开创论文，提出多尺度卷积模块《Going deeper with convolutions》
4. arXiv-2015，googlenet v2: 神经网络大杀器：BN层提出
《Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift》
5. CVPR-2016，googlenet v3: 卷积分解及结构进化，超越人类精度
《Rethinking the Inception Architecture for Computer Vision》
6. CVPR-2016，resnet：工业界标杆模型，最具影响力的卷积神经网络
《Deep Residual Learning for Image Recognition》
7. arXiv-2016，googlenet v4: Inception与ResNet结构的尝试
《 Inception-ResNet and the Impact of Residual Connections on Learning》
8. CVPR-2017，ResNeXt：何恺明团队对ResNet重大改进
《Aggregated Residual Transformations for Deep Neural Networks》
9. CVPR-2017，densenet：ResNet的改进，2016-ILSVRC冠军
《Densely Connected Convolutional Networks》
10. TPAMI-2017，SEnet：引入注意力机制的卷积神经网络，2017-ILSVRC（最后一届）冠军
《Squeeze-and-Excitation Networks》
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