# Multi-task Mid-level Feature Alignment Network for Unsupervised Cross-Dataset Person Re-Identification

arXiv: https://arxiv.org/abs/1807.01440 · HTML: https://mlsanity.com/paper/1807.01440/

## Key facts

- Cited by 34 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Jul 2018.

## Built on by (most cited first, 30 of 34)

- [Cluster Contrast for Unsupervised Person Re-Identification](https://mlsanity.com/paper/2103.11568/) (2021)
- [ICE: Inter-instance Contrastive Encoding for Unsupervised Person Re-identification](https://mlsanity.com/paper/2103.16364/) (2021)
- [Part-based Pseudo Label Refinement for Unsupervised Person Re-identification](https://mlsanity.com/paper/2203.14675/) (2022)
- [Intra-Inter Camera Similarity for Unsupervised Person Re-Identification](https://mlsanity.com/paper/2103.11658/) (2021)
- [Look Before You Leap: Improving Text-based Person Retrieval by Learning A Consistent Cross-modal Common Manifold](https://mlsanity.com/paper/2209.06209/) (2022)
- [ObjectRelator: Enabling Cross-View Object Relation Understanding Across Ego-Centric and Exo-Centric Perspectives](https://mlsanity.com/paper/2411.19083/) (2024)
- [Multi-Memory Matching for Unsupervised Visible-Infrared Person Re-Identification](https://mlsanity.com/paper/2401.06825/) (2024)
- [Learning Domain Invariant Representations for Generalizable Person Re-Identification](https://mlsanity.com/paper/2103.15890/) (2021)
- [Towards Discriminative Representation Learning for Unsupervised Person Re-identification](https://mlsanity.com/paper/2108.03439/) (2021)
- [Lifelong Unsupervised Domain Adaptive Person Re-identification with Coordinated Anti-forgetting and Adaptation](https://mlsanity.com/paper/2112.06632/) (2021)
- [Debiased Batch Normalization via Gaussian Process for Generalizable Person Re-Identification](https://mlsanity.com/paper/2203.01723/) (2022)
- [Generalizable Person Re-Identification via Self-Supervised Batch Norm Test-Time Adaption](https://mlsanity.com/paper/2203.00672/) (2022)
- [DEX: Domain Embedding Expansion for Generalized Person Re-identification](https://mlsanity.com/paper/2110.11391/) (2021)
- [Unsupervised Person Re-Identification: A Systematic Survey of Challenges and Solutions](https://mlsanity.com/paper/2109.06057/) (2021)
- [Learning Invariance from Generated Variance for Unsupervised Person Re-identification](https://mlsanity.com/paper/2301.00725/) (2023)
- [Unsupervised Person Re-Identification with Multi-Label Learning Guided Self-Paced Clustering](https://mlsanity.com/paper/2103.04580/) (2021)
- [Unsupervised and self-adaptative techniques for cross-domain person re-identification](https://mlsanity.com/paper/2103.11520/) (2021)
- [Meta Clustering Learning for Large-scale Unsupervised Person Re-identification](https://mlsanity.com/paper/2111.10032/) (2021)
- [Domain-Class Correlation Decomposition for Generalizable Person Re-Identification](https://mlsanity.com/paper/2106.15206/) (2021)
- [Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action Recognition](https://mlsanity.com/paper/2207.09767/) (2022)
- [A Unified Deep Semantic Expansion Framework for Domain-Generalized Person Re-identification](https://mlsanity.com/paper/2410.08456/) (2024)
- [Unsupervised Domain Adaptive Learning via Synthetic Data for Person Re-identification](https://mlsanity.com/paper/2109.05542/) (2021)
- [Improving Unsupervised Domain Adaptive Re-Identification via Source-Guided Selection of Pseudo-Labeling Hyperparameters](https://mlsanity.com/paper/2110.07897/) (2021)
- [A formal approach to good practices in Pseudo-Labeling for Unsupervised Domain Adaptive Re-Identification](https://mlsanity.com/paper/2112.12887/) (2021)
- [Leveraging Ensembles and Self-Supervised Learning for Fully-Unsupervised Person Re-Identification and Text Authorship Attribution](https://mlsanity.com/paper/2202.03126/) (2022)
- [Disentanglement-based Cross-Domain Feature Augmentation for Effective Unsupervised Domain Adaptive Person Re-identification](https://mlsanity.com/paper/2103.13917/) (2021)
- [Unsupervised clothing change adaptive person ReID](https://mlsanity.com/paper/2109.03702/) (2021)
- [Instance-level Heterogeneous Domain Adaptation for Limited-labeled Sketch-to-Photo Retrieval](https://mlsanity.com/paper/2211.14515/) (2022)
- [Neighbour Consistency Guided Pseudo-Label Refinement for Unsupervised Person Re-Identification](https://mlsanity.com/paper/2211.16847/) (2022)
- [CORE-ReID: Comprehensive Optimization and Refinement through Ensemble fusion in Domain Adaptation for person re-identification](https://mlsanity.com/paper/2508.03064/) (2025)

## Abstract (arXiv)

Most existing person re-identification (Re-ID) approaches follow a supervised learning framework, in which a large number of labelled matching pairs are required for training. Such a setting severely limits their scalability in real-world applications where no labelled samples are available during the training phase. To overcome this limitation, we develop a novel unsupervised Multi-task Mid-level Feature Alignment (MMFA) network for the unsupervised cross-dataset person re-identification task. Under the assumption that the source and target datasets share the same set of mid-level semantic attributes, our proposed model can be jointly optimised under the person's identity classification and the attribute learning task with a cross-dataset mid-level feature alignment regularisation term. In this way, the learned feature representation can be better generalised from one dataset to another which further improve the person re-identification accuracy. Experimental results on four benchmark datasets demonstrate that our proposed method outperforms the state-of-the-art baselines.