# Domain Adaptation through Synthesis for Unsupervised Person Re-identification

arXiv: https://arxiv.org/abs/1804.10094 · HTML: https://mlsanity.com/paper/1804.10094/

## Key facts

- Cited by 44 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Apr 2018.

## Built on by (most cited first, 30 of 44)

- [Fake It Till You Make It: Face analysis in the wild using synthetic data alone](https://mlsanity.com/paper/2109.15102/) (2021)
- [Eliminate Deviation with Deviation for Data Augmentation and a General Multi-modal Data Learning Method](https://mlsanity.com/paper/2101.08533/) (2021)
- [Synthetic Data in Human Analysis: A Survey](https://mlsanity.com/paper/2208.09191/) (2022)
- [Deep learning-based person re-identification methods: A survey and outlook of recent works](https://mlsanity.com/paper/2110.04764/) (2021)
- [Learning Domain Invariant Representations for Generalizable Person Re-Identification](https://mlsanity.com/paper/2103.15890/) (2021)
- [Less is More: Learning from Synthetic Data with Fine-grained Attributes for Person Re-Identification](https://mlsanity.com/paper/2109.10498/) (2021)
- [Cluster-guided Asymmetric Contrastive Learning for Unsupervised Person Re-Identification](https://mlsanity.com/paper/2106.07846/) (2021)
- [Semantic-aware Consistency Network for Cloth-changing Person Re-Identification](https://mlsanity.com/paper/2308.14113/) (2023)
- [Cloning Outfits from Real-World Images to 3D Characters for Generalizable Person Re-Identification](https://mlsanity.com/paper/2204.02611/) (2022)
- [PSP-HDRI+: A Synthetic Dataset Generator for Pre-Training of Human-Centric Computer Vision Models](https://mlsanity.com/paper/2207.05025/) (2022)
- [DEJA VU: Continual Model Generalization For Unseen Domains](https://mlsanity.com/paper/2301.10418/) (2023)
- [Let There be Light: Improved Traffic Surveillance via Detail Preserving Night-to-Day Transfer](https://mlsanity.com/paper/2105.05011/) (2021)
- [PeopleSansPeople: A Synthetic Data Generator for Human-Centric Computer Vision](https://mlsanity.com/paper/2112.09290/) (2021)
- [Pseudo-Pair based Self-Similarity Learning for Unsupervised Person Re-identification](https://mlsanity.com/paper/2207.13035/) (2022)
- [Human Image Generation: A Comprehensive Survey](https://mlsanity.com/paper/2212.08896/) (2022)
- [Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network](https://mlsanity.com/paper/2107.12858/) (2021)
- [Debiased Batch Normalization via Gaussian Process for Generalizable Person Re-Identification](https://mlsanity.com/paper/2203.01723/) (2022)
- [UltraPose: Synthesizing Dense Pose with 1 Billion Points by Human-body Decoupling 3D Model](https://mlsanity.com/paper/2110.15267/) (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)
- [Domain Adaptation in Multi-View Embedding for Cross-Modal Video Retrieval](https://mlsanity.com/paper/2110.12812/) (2021)
- [AttMOT: Improving Multiple-Object Tracking by Introducing Auxiliary Pedestrian Attributes](https://mlsanity.com/paper/2308.07537/) (2023)
- [WheelPose: Data Synthesis Techniques to Improve Pose Estimation Performance on Wheelchair Users](https://mlsanity.com/paper/2404.17063/) (2024)
- [Domain-Class Correlation Decomposition for Generalizable Person Re-Identification](https://mlsanity.com/paper/2106.15206/) (2021)
- [A Benchmark of Video-Based Clothes-Changing Person Re-Identification](https://mlsanity.com/paper/2211.11165/) (2022)
- [Alice Benchmarks: Connecting Real World Re-Identification with the Synthetic](https://mlsanity.com/paper/2310.04416/) (2023)
- [An Open-World, Diverse, Cross-Spatial-Temporal Benchmark for Dynamic Wild Person Re-Identification](https://mlsanity.com/paper/2403.15119/) (2024)
- [Unsupervised Person Re-Identification with Wireless Positioning under Weak Scene Labeling](https://mlsanity.com/paper/2110.15610/) (2021)
- [Unsupervised Domain Adaptive Learning via Synthetic Data for Person Re-identification](https://mlsanity.com/paper/2109.05542/) (2021)
- [TAGPerson: A Target-Aware Generation Pipeline for Person Re-identification](https://mlsanity.com/paper/2112.14239/) (2021)

## Abstract (arXiv)

Drastic variations in illumination across surveillance cameras make the person re-identification problem extremely challenging. Current large scale re-identification datasets have a significant number of training subjects, but lack diversity in lighting conditions. As a result, a trained model requires fine-tuning to become effective under an unseen illumination condition. To alleviate this problem, we introduce a new synthetic dataset that contains hundreds of illumination conditions. Specifically, we use 100 virtual humans illuminated with multiple HDR environment maps which accurately model realistic indoor and outdoor lighting. To achieve better accuracy in unseen illumination conditions we propose a novel domain adaptation technique that takes advantage of our synthetic data and performs fine-tuning in a completely unsupervised way. Our approach yields significantly higher accuracy than semi-supervised and unsupervised state-of-the-art methods, and is very competitive with supervised techniques.