🔥 Research Papers Review & Implementation

Hello!

This is a repository for deep learning research papers review and pytorch implementation. Various subjects including image classification, object detection, semantic segmentation, backbones, augmetnations are covered.

My goal is to provide thorough guide as well as intuitive implementation as I often have hard time searching through the internet for details.

If you want to see other materials, check out my blog.

Dev Blog: https://noisrucer.github.io/

📃 Covered papers

• AlexNet
• Cascade R-CNN
• CutMix
• EfficientNet
• FPN
• ResNet
• Retinanet
• Swin Transformer
• U-Net
• ViT
• WBF
• YOLOv1
• YOLOv2
• BiSeNet
• HOTR
• BMVOS

📂 Structure

Each paper is assigned to each folder.

• paper_name/
  • paper_name.ipynb: In each folder, there's a .ipynb file which is a complete paper review.
  • code/: In each folder, there's a sub-folder named code/ which stores pytorch implementation of the paper.

Some of the papers may not have .ipynb or code/ but I'm working on providing the full resources as soon as possible.

Any feedbacks are always welcome!