Summary of Face Detection: Present State and Research Directions, by Purnendu Prabhat et al.
Face Detection: Present State and Research Directions
by Purnendu Prabhat, Himanshu Gupta, Ajeet Kumar Vishwakarma
First submitted to arxiv on: 6 Feb 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This review paper presents a comprehensive overview of the current state-of-the-art in face detection, highlighting both advancements and remaining challenges. It proposes future research directions to further improve the accuracy and speed of face detection algorithms, which are essential components of many computer vision applications featuring humans. The paper reviews the existing literature on face detection, identifying areas that require more attention and outlining potential avenues for innovation. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Face detection is a crucial step in many computer vision applications that involve human faces. Despite significant research efforts, face detection still has its limitations. This paper looks at what’s been done so far and what needs to be improved. It suggests new ways to make face detection more accurate and faster, which can help with things like recognizing people in photos or videos. |
Keywords
* Artificial intelligence * Attention
