# Person Re-ID through Unsupervised Hypergraph Rank Selection and Fusion

arXiv: https://arxiv.org/abs/2304.14321 · HTML: https://mlsanity.com/paper/2304.14321/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 34 of its 91 references that are in the map.
- First posted on arXiv 27 Apr 2023.

## Builds on (most cited first, 30 of 34)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [MobileNetV2: Inverted Residuals and Linear Bottlenecks](https://mlsanity.com/paper/1801.04381/) (2018)
- [Deep Learning for Person Re-identification: A Survey and Outlook](https://mlsanity.com/paper/2001.04193/) (2020)
- [Person Transfer GAN to Bridge Domain Gap for Person Re-Identification](https://mlsanity.com/paper/1711.08565/) (2017)
- [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)
- [Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro](https://mlsanity.com/paper/1701.07717/) (2017)
- [Re-ranking Person Re-identification with k-reciprocal Encoding](https://mlsanity.com/paper/1701.08398/) (2017)
- [Harmonious Attention Network for Person Re-Identification](https://mlsanity.com/paper/1802.08122/) (2018)
- [Person Re-identification: Past, Present and Future](https://mlsanity.com/paper/1610.02984/) (2016)
- [Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification](https://mlsanity.com/paper/1711.07027/) (2017)
- [Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification](https://mlsanity.com/paper/1904.01990/) (2019)
- [Unsupervised Person Re-identification via Softened Similarity Learning](https://mlsanity.com/paper/2004.03547/) (2020)
- [Learning Generalisable Omni-Scale Representations for Person Re-Identification](https://mlsanity.com/paper/1910.06827/) (2019)
- [Multi-Level Factorisation Net for Person Re-Identification](https://mlsanity.com/paper/1803.09132/) (2018)
- [AANet: Attribute Attention Network for Person Re-Identifications](https://mlsanity.com/paper/1912.09021/) (2019)
- [Unsupervised Tracklet Person Re-Identification](https://mlsanity.com/paper/1903.00535/) (2019)
- [Unsupervised Person Re-identification by Soft Multilabel Learning](https://mlsanity.com/paper/1903.06325/) (2019)
- [Unsupervised Person Re-identification by Deep Learning Tracklet Association](https://mlsanity.com/paper/1809.02874/) (2018)
- [Torchreid: A Library for Deep Learning Person Re-Identification in Pytorch](https://mlsanity.com/paper/1910.10093/) (2019)
- [Unsupervised Multi-Source Domain Adaptation for Person Re-Identification](https://mlsanity.com/paper/2104.12961/) (2021)
- [Cross-view Asymmetric Metric Learning for Unsupervised Person Re-identification](https://mlsanity.com/paper/1708.08062/) (2017)
- [Learning a Discriminative Null Space for Person Re-identification](https://mlsanity.com/paper/1603.02139/) (2016)
- [Unsupervised Person Re-identification by Deep Asymmetric Metric Embedding](https://mlsanity.com/paper/1901.10177/) (2019)
- [EANet: Enhancing Alignment for Cross-Domain Person Re-identification](https://mlsanity.com/paper/1812.11369/) (2018)
- [Intra-Camera Supervised Person Re-Identification: A New Benchmark](https://mlsanity.com/paper/1908.10344/) (2019)
- [Domain Adaptive Person Re-Identification via Camera Style Generation and Label Propagation](https://mlsanity.com/paper/1905.05382/) (2019)
- [Intra-Camera Supervised Person Re-Identification](https://mlsanity.com/paper/2002.05046/) (2020)
- [Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification](https://mlsanity.com/paper/1804.09347/) (2018)
- [Cross-Camera Feature Prediction for Intra-Camera Supervised Person Re-identification across Distant Scenes](https://mlsanity.com/paper/2107.13904/) (2021)

## Built on by (most cited first, 1 of 1)

- [Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation](https://mlsanity.com/paper/2606.17406/) (2026)

## Abstract (arXiv)

Person Re-ID has been gaining a lot of attention and nowadays is of fundamental importance in many camera surveillance applications. The task consists of identifying individuals across multiple cameras that have no overlapping views. Most of the approaches require labeled data, which is not always available, given the huge amount of demanded data and the difficulty of manually assigning a class for each individual. Recently, studies have shown that re-ranking methods are capable of achieving significant gains, especially in the absence of labeled data. Besides that, the fusion of feature extractors and multiple-source training is another promising research direction not extensively exploited. We aim to fill this gap through a manifold rank aggregation approach capable of exploiting the complementarity of different person Re-ID rankers. In this work, we perform a completely unsupervised selection and fusion of diverse ranked lists obtained from multiple and diverse feature extractors. Among the contributions, this work proposes a query performance prediction measure that models the relationship among images considering a hypergraph structure and does not require the use of any labeled data. Expressive gains were obtained in four datasets commonly used for person Re-ID. We achieved results competitive to the state-of-the-art in most of the scenarios.