README.md

Research Paper Archive

This will be a community-driven repository where people contribute by sharing their thoughts on different research papers they have come across as a simple readme file. This would benefit the contributors by acting as a documentation for future reference and once this archive becomes decently big it would benefit the larger community as a whole. There is no restriction regarding what papers you can add onto this archive - can be old, new anything. Hope this repository gets some good contributions. Happy reading :)

To contribute

• Fork the repository
• Add the required files as described below.
• Make a pull request (everything will be merged)

REPOSITORY Layout

.
├── README.md               # Entry point to view all available papers in the archive. 
├── <PAPER-1> (a folder) `  # Every paper must be inside a folder titled as the paper name
    ├── assets              # Folder to contain images used in the README file to summarise the paper.
    └── README.md           # README file containing the summary itself.
├── <PAPER-2>
    ├── assets
    └── README.md
├── <PAPER-3>
    ├── assets
    └── README.md

Contents

• Computer Vision

  • U-Net: Convolutional Networks for Biomedical Image Segmentation
  • UNet++: A Nested U-Net Architecture for Medical Image Segmentation
  • PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
  • StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
  • StyleGAN: A Style-Based Generator Architecture for Generative Adversarial Networks
  • Image Inpainting - Generative Image Inpainting with Contextual Attention
  • Pix2Pix - Image-to-Image Translation with Conditional Adversarial Networks
  • YOLO - You Only Look Once: Unified, Real-Time Object Detection
  • Semantic Segmentation - Pyramid Scene Parsing Network
  • DINO: Emerging Properties in Self-Supervised Vision Transformers
  • 3D-R2N2_ A Unified Approach for Single and Multi-view 3D Object Reconstruction
  • DeepSDF_ Learning Continuous Signed Distance Functions for Shape Representation
  • Improved Adversarial Systems for 3D Object Generation and Reconstruction
  • Improved Protein Structure Prediction Using Potentials From Deep Learning
  • Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction
  • Learning Implicit Fields for Generative Shape Modeling
  • Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
  • Occupancy Networks_ Learning 3D Reconstruction in Function Space
  • Pix2Vox++_ Multi-scale Context-aware 3D Object Reconstruction from Single and Multiple Images
  • Robust Attentional Aggregation of Deep Feature Sets for Multi-view 3D Reconstruction

• Natural Language Processing

  • BERT - Pre-training of Deep Bidirectional Transformers for Language Understanding
  • DrQA - Reading Wikipedia to Answer Open-Domain Questions
  • Knowing When To Look - Adaptive attention for image captioning
  • Meshed-Memory Transformer for Image Captioning
  • Knowing When To Look - Adaptive attention for image captioning

• Reinforcement Learning

  • Asynchronous Methods for Deep Reinforcement Learning
  • DQN - Playing Atari with Deep Reinforcement Learning
  • DRQN - Deep Recurrent Q-Learning for Partially Observable MDPs
  • PPO - Proximal Policy Optimization Algorithms
  • Learning to Paint With Model-based Deep Reinforcement Learning

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NOTE

• Please ensure that you create an entry point to the summary on the main README FILE (this one).
• Create seperate folders for each paper to add to the repository and keep a seperate folder inside each called assets for any images used in your summary.
• In case of any error in any of the summaries, feel free to open an issue stating the paper name and what you think is the problem with the summary!!