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-Duke MTMC (Multi-Target, Multi-Camera) is a dataset of surveillance video footage taken on Duke University's campus in 2014 and is used for research and development of video tracking systems, person re-identification, and low-resolution facial recognition. The dataset contains over 14 hours of synchronized surveillance video from 8 cameras at 1080p and 60FPS with over 2 million frames of 2,000 students walking to and from classes. The 8 surveillance cameras deployed on campus were specifically setup to capture students "during periods between lectures, when pedestrian traffic is heavy"[^duke_mtmc_orig].
+Duke MTMC (Multi-Target, Multi-Camera) is a dataset of surveillance video footage taken on Duke University's campus in 2014 and is used for research and development of video tracking systems, person re-identification, and low-resolution facial recognition. The dataset contains over 14 hours of synchronized surveillance video from 8 cameras at 1080p and 60 FPS, with over 2 million frames of 2,000 students walking to and from classes. The 8 surveillance cameras deployed on campus were specifically setup to capture students "during periods between lectures, when pedestrian traffic is heavy"[^duke_mtmc_orig].
 
 In this investigation into the Duke MTMC dataset we tracked down over 100 publicly available research papers that explicitly acknowledged using Duke MTMC. Our analysis shows that the dataset has spread far beyond its origins and intentions in academic research projects at Duke University. Since its publication in 2016, more than twice as many research citations originated in China as in the United States. Among these citations were papers with explicit and direct links to the Chinese military and several of the companies known to provide Chinese authorities with the oppressive surveillance technology used to monitor millions of Uighur Muslims.
 
@@ -42,7 +42,7 @@ Despite [repeated](https://www.hrw.org/news/2017/11/19/china-police-big-data-sys
 | SenseNets, SenseTime | Attention-Aware Compositional Network for Person Re-identification | [SemanticScholar](https://www.semanticscholar.org/paper/Attention-Aware-Compositional-Network-for-Person-Xu-Zhao/14ce502bc19b225466126b256511f9c05cadcb6e) | 2018 | ✔ |
 |SenseTime| End-to-End Deep Kronecker-Product Matching for Person Re-identification | [thcvf.com](http://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_End-to-End_Deep_Kronecker-Product_CVPR_2018_paper.pdf) | 2018| ✔ |
 
-The reasons that companies in China use the Duke MTMC dataset for research are technically no different than the reasons it is used in the United States and Europe. In fact, the original creators of the dataset published a follow up report in 2017 titled [Tracking Social Groups Within and Across Cameras](https://www.semanticscholar.org/paper/Tracking-Social-Groups-Within-and-Across-Cameras-Solera-Calderara/9e644b1e33dd9367be167eb9d832174004840400) with specific applications to "automated analysis of crowds and social gatherings for surveillance and security applications". Their work, as well as the creation of the original dataset in 2014 were both supported in part by the United States Army Research Laboratory.
+The reasons that companies in China use the Duke MTMC dataset for research are technically no different than the reasons it is used in the United States and Europe. In fact, the original creators of the dataset published a follow up report in 2017 titled "[Tracking Social Groups Within and Across Cameras](https://www.semanticscholar.org/paper/Tracking-Social-Groups-Within-and-Across-Cameras-Solera-Calderara/9e644b1e33dd9367be167eb9d832174004840400)" with specific applications to "automated analysis of crowds and social gatherings for surveillance and security applications". Their work, as well as the creation of the original dataset in 2014 were both supported in part by the United States Army Research Laboratory.
 
 Citations from the United States and Europe show a similar trend to that in China, including publicly acknowledged and verified usage of the Duke MTMC dataset supported or carried out by the United States Department of Homeland Security, IARPA, IBM, Microsoft (who has provided surveillance to ICE), and Vision Semantics (who has worked with the UK Ministry of Defence). One [paper](https://pdfs.semanticscholar.org/59f3/57015054bab43fb8cbfd3f3dbf17b1d1f881.pdf) is even jointly published by researchers affiliated with both the University College of London and the National University of Defense Technology in China.