Paper-Reading

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Lists

1. Fully Convolutional Networks for Semantic Segmentation (FCN)
2. Faster-RCNN : Towards Real-Time Object Detection with Region Proposal Networks (Faster R-CNN)
3. You Only Look Once: Unified, Real-Time Object Detection (YOLO)
4. SSD: Single Shot MultiBox Detector (SSD)
5. Deformable Convolutional Networks
6. Generative Adversarial Networks (GAN)
7. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks (DCGAN)
8. InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets (InfoGAN)
9. Focal Loss for Dense Object Detection (RetinaNet)
10. Mask R-CNN
11. Light-Head R-CNN: In Defense of Two-Stage Object Detector (Light-Head R-CNN)
12. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks (CycleGAN)
13. Unsupervised Cross-Domain Image Generation (DTN, UCDIG)
14. Conditional Generative Adversarial Nets (CGAN)
15. Learning from Simulated and Unsupervised Images through Adversarial Training (SimGAN)
16. Energy-Based Generative Adversarial Networks (EBGAN)
17. Improved Techniques for Training GANs
18. ImageNet Classification with Deep Convolutional Neural Networks (AlexNet)
19. Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network (SRGAN)