# Multi-Target, Multi-Camera Tracking by Hierarchical Clustering: Recent Progress on DukeMTMC Project

arXiv: https://arxiv.org/abs/1712.09531 · HTML: https://mlsanity.com/paper/1712.09531/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Dec 2017.

## Built on by (most cited first, 19 of 19)

- [State Space Model for New-Generation Network Alternative to Transformers: A Survey](https://mlsanity.com/paper/2404.09516/) (2024)
- [DyGLIP: A Dynamic Graph Model with Link Prediction for Accurate Multi-Camera Multiple Object Tracking](https://mlsanity.com/paper/2106.06856/) (2021)
- [Multi-Camera Multiple 3D Object Tracking on the Move for Autonomous Vehicles](https://mlsanity.com/paper/2204.09151/) (2022)
- [Split and Connect: A Universal Tracklet Booster for Multi-Object Tracking](https://mlsanity.com/paper/2105.02426/) (2021)
- [DIVOTrack: A Novel Dataset and Baseline Method for Cross-View Multi-Object Tracking in DIVerse Open Scenes](https://mlsanity.com/paper/2302.07676/) (2023)
- [Multi-Target Multi-Camera Tracking of Vehicles using Metadata-Aided Re-ID and Trajectory-Based Camera Link Model](https://mlsanity.com/paper/2105.01213/) (2021)
- [Online Clustering-based Multi-Camera Vehicle Tracking in Scenarios with overlapping FOVs](https://mlsanity.com/paper/2102.04091/) (2021)
- [Multi-Camera Multi-Object Tracking on the Move via Single-Stage Global Association Approach](https://mlsanity.com/paper/2211.09663/) (2022)
- [Multiple Object Tracking from appearance by hierarchically clustering tracklets](https://mlsanity.com/paper/2210.03355/) (2022)
- [Tracking by Associating Clips](https://mlsanity.com/paper/2212.10149/) (2022)
- [MTMMC: A Large-Scale Real-World Multi-Modal Camera Tracking Benchmark](https://mlsanity.com/paper/2403.20225/) (2024)
- [Knowledge Distillation for Multi-Target Domain Adaptation in Real-Time Person Re-Identification](https://mlsanity.com/paper/2205.06237/) (2022)
- [Adaptive Affinity for Associations in Multi-Target Multi-Camera Tracking](https://mlsanity.com/paper/2112.07664/) (2021)
- [SCING:Towards More Efficient and Robust Person Re-Identification through Selective Cross-modal Prompt Tuning](https://mlsanity.com/paper/2507.00506/) (2025)
- [Online 3D Multi-Camera Perception through Robust 2D Tracking and Depth-based Late Aggregation](https://mlsanity.com/paper/2509.09946/) (2025)
- [Tracklet-Switch Adversarial Attack against Pedestrian Multi-Object Tracking Trackers](https://mlsanity.com/paper/2111.08954/) (2021)
- [Towards Effective Multi-Moving-Camera Tracking: A New Dataset and Lightweight Link Model](https://mlsanity.com/paper/2312.11035/) (2023)
- [Mitigating Downstream Model Risks via Model Provenance](https://mlsanity.com/paper/2410.02230/) (2024)
- [Multi Camera Connected Vision System with Multi View Analytics: A Comprehensive Survey](https://mlsanity.com/paper/2510.09731/) (2025)

## Abstract (arXiv)

Although many methods perform well in single camera tracking, multi-camera tracking remains a challenging problem with less attention. DukeMTMC is a large-scale, well-annotated multi-camera tracking benchmark which makes great progress in this field. This report is dedicated to briefly introduce our method on DukeMTMC and show that simple hierarchical clustering with well-trained person re-identification features can get good results on this dataset.