# A Spatial-Temporal Transformer based Framework For Human Pose Assessment And Correction in Education Scenarios

arXiv: https://arxiv.org/abs/2311.00401 · HTML: https://mlsanity.com/paper/2311.00401/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 18 of its 27 references that are in the map.
- First posted on arXiv 1 Nov 2023.

## Builds on (most cited first, 18 of 18)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks](https://mlsanity.com/paper/1506.01497/) (2015)
- [Fully Convolutional Networks for Semantic Segmentation](https://mlsanity.com/paper/1411.4038/) (2014)
- [CBAM: Convolutional Block Attention Module](https://mlsanity.com/paper/1807.06521/) (2018)
- [Deep High-Resolution Representation Learning for Visual Recognition](https://mlsanity.com/paper/1908.07919/) (2019)
- [Deep High-Resolution Representation Learning for Human Pose Estimation](https://mlsanity.com/paper/1902.09212/) (2019)
- [Objects as Points](https://mlsanity.com/paper/1904.07850/) (2019)
- [OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields](https://mlsanity.com/paper/1812.08008/) (2018)
- [Stacked Hourglass Networks for Human Pose Estimation](https://mlsanity.com/paper/1603.06937/) (2016)
- [Convolutional Pose Machines](https://mlsanity.com/paper/1602.00134/) (2016)
- [3D Human Pose Estimation with Spatial and Temporal Transformers](https://mlsanity.com/paper/2103.10455/) (2021)
- [What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment](https://mlsanity.com/paper/1904.04346/) (2019)
- [Action Quality Assessment Across Multiple Actions](https://mlsanity.com/paper/1812.06367/) (2018)
- [The Pros and Cons: Rank-aware Temporal Attention for Skill Determination in Long Videos](https://mlsanity.com/paper/1812.05538/) (2018)
- [Manipulation-skill Assessment from Videos with Spatial Attention Network](https://mlsanity.com/paper/1901.02579/) (2019)
- [Lite Pose: Efficient Architecture Design for 2D Human Pose Estimation](https://mlsanity.com/paper/2205.01271/) (2022)
- [Human Pose Estimation using Global and Local Normalization](https://mlsanity.com/paper/1709.07220/) (2017)

## Abstract (arXiv)

Human pose assessment and correction play a crucial role in applications across various fields, including computer vision, robotics, sports analysis, healthcare, and entertainment. In this paper, we propose a Spatial-Temporal Transformer based Framework (STTF) for human pose assessment and correction in education scenarios such as physical exercises and science experiment. The framework comprising skeletal tracking, pose estimation, posture assessment, and posture correction modules to educate students with professional, quick-to-fix feedback. We also create a pose correction method to provide corrective feedback in the form of visual aids. We test the framework with our own dataset. It comprises (a) new recordings of five exercises, (b) existing recordings found on the internet of the same exercises, and (c) corrective feedback on the recordings by professional athletes and teachers. Results show that our model can effectively measure and comment on the quality of students' actions. The STTF leverages the power of transformer models to capture spatial and temporal dependencies in human poses, enabling accurate assessment and effective correction of students' movements.