https://github.com/hoya012/cvpr-2020-paper-statistics
Statistics and Visualization of acceptance rate, main keyword of CVPR 2020 accepted papers for the main Computer Vision conference (CVPR)
https://github.com/hoya012/cvpr-2020-paper-statistics
Last synced: 17 days ago
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Statistics and Visualization of acceptance rate, main keyword of CVPR 2020 accepted papers for the main Computer Vision conference (CVPR)
- Host: GitHub
- URL: https://github.com/hoya012/cvpr-2020-paper-statistics
- Owner: hoya012
- Created: 2020-05-21T07:12:37.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2021-05-24T07:54:27.000Z (over 4 years ago)
- Last Synced: 2025-07-20T11:47:36.943Z (3 months ago)
- Language: Jupyter Notebook
- Size: 1.95 MB
- Stars: 33
- Watchers: 4
- Forks: 4
- Open Issues: 1
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Metadata Files:
- Readme: README.md
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README
# CVPR-2020 Paper-Statistics
Statistics and Visualization of acceptance rate, main keyword of CVPR 2020 accepted papers for the main Computer Vision conference [(CVPR 2020)](http://cvpr2020.thecvf.com/)
Inspired by [`CVPR-2019-Paper-Statistics`](https://github.com/hoya012/CVPR-2019-Paper-Statistics)
# CVPR 2020 Acceptance rate (2016~2020)
- The total number of papers is increasing every year and this year has increased significantly!
- The acceptance rate decreased from 25% to 22%.
# CVPR 2020 Paper Keywords statistics
- Most of the top keywords were maintained
- Image, detection, 3d, object, video, segmentation, adversarial, recognition, visual …
- `search`, `self-supervised`, `semi-supervised` are about twice as frequent
- search : 18 -> 39
- self-supervised: 12 -> 33
- semi-supervised: 12 -> 25
# Analysis and Visualization Code (Jupyter Notebook)
- The above data can be obtained from a simple jupyter notebook script.
- [`CVPR_paper_statistics_using_chrome.ipynb`](https://github.com/hoya012/CVPR-2020-Paper-Statistics/blob/master/2020_cvpr/CVPR2020_paper_statistics_using_chrome.ipynb) --> Use website data format
## Prerequisites
- python3.5
- [selenium](https://selenium-python.readthedocs.io/)
- [wordcloud](https://pypi.org/project/wordcloud/)
- [matplotlib](https://matplotlib.org/)
or
**i highly recommend to use** [google colab](https://colab.research.google.com/)
Just **download jupyter notebook** and **move to your google drive** and **Open with Colaboratory**