# A Topology-Aware Graph Convolutional Network for Human Pose Similarity and Action Quality Assessment

arXiv: https://arxiv.org/abs/2511.01194 · HTML: https://mlsanity.com/paper/2511.01194/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 14 of its 24 references that are in the map.
- First posted on arXiv 3 Nov 2025.

## Builds on (most cited first, 14 of 14)

- [Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition](https://mlsanity.com/paper/1801.07455/) (2018)
- [Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting](https://mlsanity.com/paper/1709.04875/) (2017)
- [NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis](https://mlsanity.com/paper/1604.02808/) (2016)
- [FineDiving: A Fine-grained Dataset for Procedure-aware Action Quality Assessment](https://mlsanity.com/paper/2204.03646/) (2022)
- [Group-aware Contrastive Regression for Action Quality Assessment](https://mlsanity.com/paper/2108.07797/) (2021)
- [Action Quality Assessment with Temporal Parsing Transformer](https://mlsanity.com/paper/2207.09270/) (2022)
- [Feedback Graph Convolutional Network for Skeleton-based Action Recognition](https://mlsanity.com/paper/2003.07564/) (2020)
- [A Comprehensive Survey of Action Quality Assessment: Method and Benchmark](https://mlsanity.com/paper/2412.11149/) (2024)
- [AthletePose3D: A Benchmark Dataset for 3D Human Pose Estimation and Kinematic Validation in Athletic Movements](https://mlsanity.com/paper/2503.07499/) (2025)
- [Deep learning for 3D human pose estimation and mesh recovery: A survey](https://mlsanity.com/paper/2402.18844/) (2024)
- [A Survey on 3D Egocentric Human Pose Estimation](https://mlsanity.com/paper/2403.17893/) (2024)
- [A Decade of Action Quality Assessment: Largest Systematic Survey of Trends, Challenges, and Future Directions](https://mlsanity.com/paper/2502.02817/) (2025)
- [DFM: Deep Fourier Mimic for Expressive Dance Motion Learning](https://mlsanity.com/paper/2502.10980/) (2025)
- [A survey of top-down approaches for human pose estimation](https://mlsanity.com/paper/2202.02656/) (2022)

## Abstract (arXiv)

Action Quality Assessment (AQA) requires fine-grained understanding of human motion and precise evaluation of pose similarity. This paper proposes a topology-aware Graph Convolutional Network (GCN) framework, termed GCN-PSN, which models the human skeleton as a graph to learn discriminative, topology-sensitive pose embeddings. Using a Siamese architecture trained with a contrastive regression objective, our method outperforms coordinate-based baselines and achieves competitive performance on AQA-7 and FineDiving benchmarks. Experimental results and ablation studies validate the effectiveness of leveraging skeletal topology for pose similarity and action quality assessment.