# KeyRe-ID: Keypoint-Guided Person Re-Identification using Part-Aware Representation in Videos

arXiv: https://arxiv.org/abs/2507.07393 · HTML: https://mlsanity.com/paper/2507.07393/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 18 of its 35 references that are in the map.
- First posted on arXiv 10 Jul 2025.

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

- [Rethinking the Inception Architecture for Computer Vision](https://mlsanity.com/paper/1512.00567/) (2015)
- [ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices](https://mlsanity.com/paper/1707.01083/) (2017)
- [TransReID: Transformer-based Object Re-Identification](https://mlsanity.com/paper/2102.04378/) (2021)
- [PifPaf: Composite Fields for Human Pose Estimation](https://mlsanity.com/paper/1903.06593/) (2019)
- [Human Semantic Parsing for Person Re-identification](https://mlsanity.com/paper/1804.00216/) (2018)
- [Pose-guided Feature Disentangling for Occluded Person Re-identification Based on Transformer](https://mlsanity.com/paper/2112.02466/) (2021)
- [Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification](https://mlsanity.com/paper/2104.14913/) (2021)
- [Unsupervised Person Re-identification by Deep Learning Tracklet Association](https://mlsanity.com/paper/1809.02874/) (2018)
- [Multi-Granularity Reference-Aided Attentive Feature Aggregation for Video-based Person Re-identification](https://mlsanity.com/paper/2003.12224/) (2020)
- [Spatial-Temporal Correlation and Topology Learning for Person Re-Identification in Videos](https://mlsanity.com/paper/2104.08241/) (2021)
- [Multi-direction and Multi-scale Pyramid in Transformer for Video-based Pedestrian Retrieval](https://mlsanity.com/paper/2202.06014/) (2022)
- [Cross-Platform Video Person ReID: A New Benchmark Dataset and Adaptation Approach](https://mlsanity.com/paper/2408.07500/) (2024)
- [Spatiotemporal Transformer for Video-based Person Re-identification](https://mlsanity.com/paper/2103.16469/) (2021)
- [Video Person Re-ID: Fantastic Techniques and Where to Find Them](https://mlsanity.com/paper/1912.05295/) (2019)
- [Occluded Person Re-Identification with Deep Learning: A Survey and Perspectives](https://mlsanity.com/paper/2311.00603/) (2023)
- [Global-Local Temporal Representations For Video Person Re-Identification](https://mlsanity.com/paper/1908.10049/) (2019)
- [Rethinking Temporal Fusion for Video-based Person Re-identification on Semantic and Time Aspect](https://mlsanity.com/paper/1911.12512/) (2019)
- [A Spatial and Temporal Features Mixture Model with Body Parts for Video-based Person Re-Identification](https://mlsanity.com/paper/1807.00975/) (2018)

## Abstract (arXiv)

We propose KeyRe-ID, a keypoint-guided video-based person re-identification framework consisting of global and local branches that leverage human keypoints for enhanced spatiotemporal representation learning. The global branch captures holistic identity semantics through Transformer-based temporal aggregation, while the local branch dynamically segments body regions based on keypoints to generate fine-grained, part-aware features. Extensive experiments on MARS and iLIDS-VID benchmarks demonstrate state-of-the-art performance, achieving 91.73% mAP and 97.32% Rank-1 accuracy on MARS, and 96.00% Rank-1 and 100.0% Rank-5 accuracy on iLIDS-VID. The code for this work will be publicly available on GitHub upon publication.