# Identity-Sensitive Knowledge Propagation for Cloth-Changing Person Re-identification

arXiv: https://arxiv.org/abs/2208.12023 · HTML: https://mlsanity.com/paper/2208.12023/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 22 references that are in the map.
- First posted on arXiv 25 Aug 2022.

## Builds on (most cited first, 15 of 15)

- [Distilling the Knowledge in a Neural Network](https://mlsanity.com/paper/1503.02531/) (2015)
- [In Defense of the Triplet Loss for Person Re-Identification](https://mlsanity.com/paper/1703.07737/) (2017)
- [DensePose: Dense Human Pose Estimation In The Wild](https://mlsanity.com/paper/1802.00434/) (2018)
- [Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)](https://mlsanity.com/paper/1711.09349/) (2017)
- [Omni-Scale Feature Learning for Person Re-Identification](https://mlsanity.com/paper/1905.00953/) (2019)
- [Learning Discriminative Features with Multiple Granularities for Person Re-Identification](https://mlsanity.com/paper/1804.01438/) (2018)
- [Harmonious Attention Network for Person Re-Identification](https://mlsanity.com/paper/1802.08122/) (2018)
- [GAN Prior Embedded Network for Blind Face Restoration in the Wild](https://mlsanity.com/paper/2105.06070/) (2021)
- [Self-Correction for Human Parsing](https://mlsanity.com/paper/1910.09777/) (2019)
- [Person Re-identification by Contour Sketch under Moderate Clothing Change](https://mlsanity.com/paper/2002.02295/) (2020)
- [Long-Term Cloth-Changing Person Re-identification](https://mlsanity.com/paper/2005.12633/) (2020)
- [When Person Re-identification Meets Changing Clothes](https://mlsanity.com/paper/2003.04070/) (2020)
- [COCAS: A Large-Scale Clothes Changing Person Dataset for Re-identification](https://mlsanity.com/paper/2005.07862/) (2020)
- [Semantic-guided Pixel Sampling for Cloth-Changing Person Re-identification](https://mlsanity.com/paper/2107.11522/) (2021)
- [Lightweight Multi-Branch Network for Person Re-Identification](https://mlsanity.com/paper/2101.10774/) (2021)

## Built on by (most cited first, 5 of 5)

- [Masked Attribute Description Embedding for Cloth-Changing Person Re-identification](https://mlsanity.com/paper/2401.05646/) (2024)
- [Coarse Attribute Prediction with Task Agnostic Distillation for Real World Clothes Changing ReID](https://mlsanity.com/paper/2505.12580/) (2025)
- [Enhanced Multi-Scale Cross-Attention for Person Image Generation](https://mlsanity.com/paper/2501.08900/) (2025)
- [Clothes-Changing Person Re-Identification with Feasibility-Aware Intermediary Matching](https://mlsanity.com/paper/2404.09507/) (2024)
- [TSDW: A Tri-Stream Dynamic Weight Network for Cloth-Changing Person Re-Identification](https://mlsanity.com/paper/2503.00477/) (2025)

## Abstract (arXiv)

Cloth-changing person re-identification (CC-ReID), which aims to match person identities under clothing changes, is a new rising research topic in recent years. However, typical biometrics-based CC-ReID methods often require cumbersome pose or body part estimators to learn cloth-irrelevant features from human biometric traits, which comes with high computational costs. Besides, the performance is significantly limited due to the resolution degradation of surveillance images. To address the above limitations, we propose an effective Identity-Sensitive Knowledge Propagation framework (DeSKPro) for CC-ReID. Specifically, a Cloth-irrelevant Spatial Attention module is introduced to eliminate the distraction of clothing appearance by acquiring knowledge from the human parsing module. To mitigate the resolution degradation issue and mine identity-sensitive cues from human faces, we propose to restore the missing facial details using prior facial knowledge, which is then propagated to a smaller network. After training, the extra computations for human parsing or face restoration are no longer required. Extensive experiments show that our framework outperforms state-of-the-art methods by a large margin. Our code is available at https://github.com/KimbingNg/DeskPro.