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Computer Vision Paper Reviews with Key Summary of paper, End to End Code Practice and Jupyter Notebook converted papers

License: MIT License

Jupyter Notebook 95.92% Python 4.08%
computer-vision papers paper-implementations paper-reviews deep-learning transformer object-detection image-generation segmentation representation-learning

computer-vision-paper-reviews's Introduction

Computer-Vision-Paper-Reviews

Computer Vision Paper Reviews with Key Summary along Papers & Codes.

Jonathan Choi 2021

The repository provides 100+ Papers across Computer Vision fields converted as Jupyter Notebook, with the Key Summary and End to End Code Practice.


Contents

The goal of the repository is providing an end to end study scripts of most read and important papers.

The prefered readers are not limited for researchers, but also for students and engieeners from beginner to the professions in computer vision fields .

To provide the rich understanding, each paper contains following three main contents.

Key Summary: Providing key summaries and terminologies of the paper so that even beginner can study easily and perfectly.

Code Practice: Providing an end to end study script of codes for the paper.

Jupyter Notebook edited Original Paper: Providing the Jupyter notbook converted Original Paper for easy and fast modification and understanding.


Category/Paper/

Paper_Review_Practice.ipynb includes

Key Summary according to the flow of Original Paper (Jupyter Notebook Edited) with the End to End Code Practice

Paper.ipynb includes

Original Paper (Jupyter Notebook Edited)

Review.ipynb includes

Key Summary

Practice.ipynb includes

End to End Code Practice


Visual Correspondence

NCNET - Neighbourhood consensus networks for estimating image correspondences

WeakAlign - End-to-end weakly-supervised semantic alignment


Transformers

[DETR] End-to-End Object Detection with Transformers

[Vision Transformer] An Image Is Worth 16x16 Words: Transformers For Image Recognition at Scale

Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

[Transformer] Attention Is All You Need

Vision Transformers for Dense Prediction


Object Detection

Feature Pyramid Networks for Object Detection

Selective Search for Object Recognition

R-CNN

Fast R-CNN

Faster R-CNN

Sparse R-CNN

YOLOv4: Optimal Speed and Accuracy of Object Detection


Segmentation

Panoptic Feature Pyramid Networks

Mask R-CNN

PointRend: Image Segmentation as Rendering


Representation Learning

Unsupervised Feature Learning via Non-Parametric Instance Discrimination

Momentum Contrast for Unsupervised Visual Representation Learning.

A Simple Framework for Contrastive Learning of Visual Representations

Bootstrap Your Own Latent- A New Approach to Self-supervised Learning

Exploring Simple Siamese Representation Learning


Generative Model

Generative Adversarial Networks

A Style-Based Generator Architecture for Generative Adversarial Networks

GAN Dissection: Visualizing and Understanding Generative Adversarial Networks

Semantic Image Synthesis with Spatially-Adaptive Normalization

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks


Image to Image Translation and Style Transfer

Image-to-Image Translation with Conditional Adversarial Networks (CVPR 2017)

Bi-level Feature Alignment for Versatile Image Translation and Manipulation

Instance Normalization: The Missing Ingredient for Fast Stylization

Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization

Semantic Image Synthesis with Spatially-Adaptive Normalization

Universal Style Transfer via Feature Transforms

A Neural Algorithm of Artistic Style


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