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TFW: Annotated Thermal Faces in the Wild Dataset Card
Summary:
The TFW dataset provides a collection of thermal face images captured in diverse environments: controlled indoor (c-indoor), semi-controlled indoor (s-indoor), and uncontrolled outdoor (u-outdoor). It's annotated with bounding boxes and 5-point facial landmarks. The dataset is accompanied by pre-trained YOLOv5 and YOLO5Face models for thermal face detection, trained and evaluated on the TFW data. The dataset builds upon the SpeakingFaces dataset for its c-indoor portion.
Dataset Statistics:
Environment | Subjects | Images | Labeled Faces | Visual Pair |
---|---|---|---|---|
c-indoor | 142 | 5,112 | 5,112 | yes |
s-indoor | 9 | 780 | 1,748 | yes |
u-outdoor | 15 | 4,090 | 9,649 | no |
combined | 147 | 9,982 | 16,509 | yes & no |
Example Annotated Images:
Pre-trained Models:
Model | Backbone | c-indoor AP50 | u-outdoor AP50 | Speed (ms) V100 b1 | Params (M) | Flops (G) @512x384 |
---|---|---|---|---|---|---|
YOLOv5n | CSPNet | 100 | 97.29 | 6.16 | 1.76 | 0.99 |
YOLOv5n6 | CSPNet | 100 | 95.79 | 8.18 | 3.09 | 1.02 |
YOLOv5s | CSPNet | 100 | 96.82 | 7.20 | 7.05 | 3.91 |
YOLOv5s6 | CSPNet | 100 | 96.83 | 9.05 | 12.31 | 3.88 |
YOLOv5m | CSPNet | 100 | 97.16 | 9.59 | 21.04 | 12.07 |
YOLOv5m6 | CSPNet | 100 | 97.10 | 12.11 | 35.25 | 11.76 |
YOLOv5l | CSPNet | 100 | 96.68 | 12.39 | 46.60 | 27.38 |
YOLOv5l6 | CSPNet | 100 | 96.29 | 15.73 | 76.16 | 110.2 |
YOLOv5n-Face | ShuffleNetv2 | 100 | 95.93 | 10.12 | 1.72 | 1.36 |
YOLOv5n6-Face | ShuffleNetv2 | 100 | 95.59 | 13.30 | 2.54 | 1.38 |
YOLOv5s-Face | CSPNet | 100 | 96.73 | 8.29 | 7.06 | 3.67 |
YOLOv5s6-Face | CSPNet | 100 | 96.36 | 10.86 | 12.37 | 3.75 |
YOLOv5m-Face | CSPNet | 100 | 95.32 | 11.01 | 21.04 | 11.58 |
YOLOv5m6-Face | CSPNet | 100 | 96.32 | 13.97 | 35.45 | 11.84 |
YOLOv5l-Face | CSPNet | 100 | 96.18 | 13.57 | 46.59 | 25.59 |
YOLOv5l6-Face | CSPNet | 100 | 95.76 | 17.29 | 76.67 | 113.2 |
Citation:
@ARTICLE{9781417,
author={Kuzdeuov, Askat and Aubakirova, Dana and Koishigarina, Darina and Varol, Huseyin Atakan},
journal={IEEE Transactions on Information Forensics and Security},
title={TFW: Annotated Thermal Faces in the Wild Dataset},
year={2022},
volume={17},
number={},
pages={2084-2094},
doi={10.1109/TIFS.2022.3177949}}
GitHub Repository: https://github.com/IS2AI/TFW
Paper: https://www.techrxiv.org/articles/preprint/TFW_Annotated_Thermal_Faces_in_the_Wild_Dataset/17004538 (Open Access) https://ieeexplore.ieee.org/abstract/document/9781417 (IEEE)
YouTube Video: https://www.youtube.com/watch?v=QgXi3rLv1jM
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