LearnWare - A repository for open source CV/PR/ML projects/models

Some great or awesome repositories on github - awesome-deep-vision (Strongly recommended!!!)

- "A curated list of deep learning resources for computer vision, inspired by awesome-php and awesome-computer-vision."
- Maintainers - Jiwon Kim, Heesoo Myeong, Myungsub Choi, Jung Kwon Lee, Taeksoo Kim
- [repo link](https://github.com/kjw0612/awesome-deep-vision/)
- [local copy](./awesome-deep-vision/README.md) (may not be updated timely)

• awesome-artificial-intelligence:

  • "A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers."
  • Maintainer: jbhuang1@illinois.edu
  • repo link
  • local copy (may not be updated timely)

• awesome-computer-vision

  • "A curated list of awesome computer vision resources"
  • Maintainer: jbhuang1@illinois.edu
    
  • repo link
  • local copy (may not be updated timely)

• awesome-deep-learning-papers

  • "A curated list of the most cited deep learning papers (since 2012)"
  • "We believe that there exist classic deep learning papers which are worth reading regardless of their application domain. Rather than providing overwhelming amount of papers, We would like to provide a curated list of the awesome deep learning papers which are considered as must-reads in certain research domains."
  • Maintainer: terryum
  • repo link
  • local copy (may not be updated timely)

• awesome-machine-learning

  • "A curated list of awesome machine learning frameworks, libraries and software (by language). Inspired by awesome-php."
  • Maintainer: josephmisiti
  • repo link
  • local copy (may not be updated timely)

• awesome-rnn

  • "A curated list of resources dedicated to recurrent neural networks (closely related to deep learning)."
  • Maintainers - Myungsub Choi, Taeksoo Kim, Jiwon Kim
  • repo link
  • local copy (may not be updated timely)

• awesome-random-forest

  • "Random Forest - a curated list of resources regarding tree-based methods and more, including but not limited to random forest, bagging and boosting."
  • Maintainer: kjw0612
  • repo link
  • local copy (may not be updated timely)

• Deep-Learning-Papers-Reading-Roadmap

  • "If you are a newcomer to the Deep Learning area, the first question you may have is "Which paper should I start reading from?" Here is a reading roadmap of Deep Learning papers!"
  • Maintainer: songrotek
  • repo link
  • local copy (may not be updated timely)

• AdversarialNetsPapers

  • "The classical papers and codes about generative adversarial nets"
  • Maintainer: zhangqianhui
  • repo link
  • local copy (may not be updated timely)

1. General Object Classification/Detection

• Classification

  • [paper]
  • [project/code/model]
  • [dataset]

• Detection

  • [paper]
  • [project/code/model]
  • [dataset] # 2. Face Related

• Face Detection

  • [paper]
  • [project/code/model]
  • [dataset]

• Face Recognition

  • [paper]
  • [project/code/model]
  • [dataset]

• Facical Landmarks/Keypoints detection

  • [paper]
  • [project/code/model]
  • [dataset]

• Age/Gender Recognition

  • [paper]
  • [project/code/model]
  • [dataset]

• Emotion Recognition

  • [paper]
  • [project/code/model]
  • [dataset] # 3. Content Audit

• Pulp/Porn/NSFW(Not Suitable For Work) Content Recognition

  • [paper]
  • [project/code/model]
  • [dataset]
  • Terror Content Recognition
  • [paper]
  • [project/code/model]
  • [dataset] # 4. Scenes/Places Recognition

• [paper]

• [project/code/model]

• [dataset]

  5. Others

• [paper]

• [project/code/model]

• [dataset]