[딥러닝] 논문 모음

1. Convolutional Neural Network

• LeNet5: Y LeCun. GradientBased Learning Applied to Document Recognition. IEEE 1998.

• AlexNet: A Krizhevsky. ImageNet Classification with Deep Convolutional Neural Networks. NeurIPS 2012.

• VGGNet: K Simonyan. Very Deep Convolutional Networks for Large-Scale Image Recognition. ICLR 2015.

• $1 \times 1$ Convolution: M Lin. Network in network. ICLR 2013.

  • 공부 Post

• GoogLeNet: C Szegedy. Going deeper with convolutions. CVPR 2015.

  • 공부 Post

• Batch Normalization: S loffe. Batch normalization: Accelerating deep network training by reducing internal covariate shift. ICML 2015.

  • 공부 Post

• ResNet: K He. Deep Residual Learning for Image Recognition. CVPR 2016.

  • 공부 Post
  • 논문 리뷰

• DCN: J Dai. Deformable Convolutional Networks. ICCV 2017.

2. Object Detection

• R-CNN: R Girshick. Rich feature hierarchies for accurate object detection and semantic segmentation. CVPR 2014.

  • 논문 리뷰

• Fast R-CNN: R Girshick. Fast R-CNN. ICCV 2015.

  • 논문 리뷰

• YOLO v1: J Redmon. You Only Look Once: Unified, Real-Time Object Detection. CVPR 2016.

  • 논문 리뷰

• FPN: TY Lin. Feature Pyramid Networks for Object Detection. CVPR 2017.

• Focal Loss, RetinaNet: TY Lin. Focal Loss for Dense Object Detection. ICCV 2017.

  • 공부 Post

• YOLO v3: J Redmon. YOLOv3: An Incremental Improvement. arXiv 2018.

• CenterNet: X Zhou. Objects as Points. arXiv 2019.

• CenterPoint: T Yin. Center-based 3D Object Detection and Tracking. CVPR 2021.

  • 적용 Post

• FCOS3D: T Wang. Fully Convolutional One-Stage Monocular 3D Object Detection. ICCV 2021.

3. Generative

• Diffusion: J Sohl-Dickstein. Deep Unsupervised Learning using Nonequilibrium Thermodynamics. ICML 2015.

4.

• Transformer: A Vaswani. Attention Is All You Need. NeurIPS 2017.

  • Blog Post by Google Research

  • Transformer models: an introduction and catalog