Facial Keypoints Detection
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Abstract (arXiv)
Detect facial keypoints is a critical element in face recognition. However, there is difficulty to catch keypoints on the face due to complex influences from original images, and there is no guidance to suitable algorithms. In this paper, we study different algorithms that can be applied to locate keyponits. Specifically: our framework (1)prepare the data for further investigation (2)Using PCA and LBP to process the data (3) Apply different algorithms to analysis data, including linear regression models, tree based model, neural network and convolutional neural network, etc. Finally we will give our conclusion and further research topic. A comprehensive set of experiments on dataset demonstrates the effectiveness of our framework.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Oct 2017.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 0; 2025: 0; 2026: 1.
4 papers.
- 2023Nonlinear optical encoding enabled by recurrent linear scatteringcited by 15
- 2022Revisiting Facial Key Point Detection: An Efficient Approach Using Deep Neural Networkscited by 2
- 2026Chasing the Public Score: User Pressure and Evaluation Exploitation in Coding Agent Workflowscited by 2
- 2021Geometry-Aware Hierarchical Bayesian Learning on Manifoldscited by 1
- 2026Chasing the Public Score: User Pressure and Evaluation Exploitation in Coding Agent Workflows22 Apr 2026
- 2023Nonlinear optical encoding enabled by recurrent linear scattering17 Jul 2023
- 2022Revisiting Facial Key Point Detection: An Efficient Approach Using Deep Neural Networks14 May 2022
- 2021Geometry-Aware Hierarchical Bayesian Learning on Manifolds30 Oct 2021