Inspired by Andrew Ng's advice on how to do research, I have decided to keep a master list of research papers (related to Computer Vision) that are either on my reading list or I have read so far.
| Research Paper | URL | Progress (*/10) |
|---|---|---|
| Deep Residual Learning for Image Recognition | https://arxiv.org/abs/1512.03385 | 8 |
| Squeeze-and-Excitation Networks | https://arxiv.org/abs/1709.01507 | 8 |
| Aggregated Residual Transformations for Deep Neural Networks | https://arxiv.org/abs/1611.05431 | 2 |
| Going Deeper with Convolutions | https://arxiv.org/abs/1409.4842 | 0 |
| MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications | https://arxiv.org/abs/1704.04861 | 0 |
| Self-training with Noisy Student improves ImageNet classification | https://arxiv.org/abs/1911.04252 | 4 |
| Rethinking Pre-training and Self-training | https://arxiv.org/abs/2006.06882 | 8 |
| Rethinking ImageNet Pre-training | https://arxiv.org/abs/1811.08883 | 10 |
| Densely Connected Convolutional Networks | https://arxiv.org/abs/1608.06993 | 10 |
| Group Normalization | https://arxiv.org/abs/1803.08494 | 7 |
| Weight Standardization | https://arxiv.org/abs/1903.10520 | 1 |
| Big Transfer (BiT): General Visual Representation Learning | https://arxiv.org/abs/1912.11370 | 6 |
| ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks | https://arxiv.org/abs/1910.03151 | 8 |
| EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks | https://arxiv.org/abs/1905.11946 | 9 |
| A Simple Framework for Contrastive Learning of Visual Representations | https://arxiv.org/abs/2002.05709 | 4 |
| Go Wide, Then Narrow: Efficient Training of Deep Thin Networks | https://arxiv.org/abs/2007.00811 | 4 |
| Fine-tuning CNN Image Retrieval with No Human Annotation | https://arxiv.org/abs/1711.02512 | 8 |
| 2nd Place and 2nd Place Solution to Kaggle Landmark Recognition and Retrieval Competition 2019 | https://arxiv.org/abs/1906.03990 | 5 |
| ArcFace: Additive Angular Margin Loss for Deep Face Recognition | https://arxiv.org/abs/1801.07698 | 6 |
| Unifying Deep Local and Global Features for Image Search | https://arxiv.org/abs/2001.05027 | 3 |
| A Discriminative Feature Learning Approach for Deep Face Recognition | https://kpzhang93.github.io/papers/eccv2016.pdf | 8 |