https://github.com/hoya012/cvpr-2022-paper-statistics
Statistics and Visualization of acceptance rate, main keyword of CVPR 2022 accepted papers for the main Computer Vision conference (CVPR)
https://github.com/hoya012/cvpr-2022-paper-statistics
Last synced: about 2 months ago
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Statistics and Visualization of acceptance rate, main keyword of CVPR 2022 accepted papers for the main Computer Vision conference (CVPR)
- Host: GitHub
- URL: https://github.com/hoya012/cvpr-2022-paper-statistics
- Owner: hoya012
- Created: 2023-05-04T05:28:21.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-05-04T05:57:12.000Z (over 2 years ago)
- Last Synced: 2025-07-02T03:37:36.235Z (4 months ago)
- Language: Jupyter Notebook
- Size: 1.29 MB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# CVPR-2022-Paper-Statistics
Statistics and Visualization of acceptance rate, main keyword of CVPR 2022 accepted papers for the main Computer Vision conference [(CVPR 2022)](http://cvpr2022.thecvf.com/)
Inspired by [`CVPR-2021-Paper-Statistics`](https://github.com/hoya012/CVPR-2021-Paper-Statistics)
# CVPR 2022 Acceptance rate (2018~2022)
- The total number of papers is increasing every year and this year has increased significantly! (7015 -> 8161)
- The acceptance rate increased back to 25%.
# CVPR 2022 Paper Keywords statistics
- Most of the top keywords were maintained
- image, detection, 3d, transformer, video, segmentation, representation, self-supervised, etc.
- `self-supervised` is about x1.5 as frequent
- self-supervised: 50 -> 74
# 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-2022-Paper-Statistics/blob/main/2022_cvpr/CVPR2022_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**