Thermal infrared imaging is widely used in body temperature measurement,
security monitoring, and so on, but its safety research attracted attention
only in recent years. We proposed the infrared adversarial clothing, which
could fool infrared pedestrian detectors at different angles. We simulated the
process from cloth to clothing in the digital world and then designed the
adversarial "QR code" pattern. The core of our method is to design a basic
pattern that can be expanded periodically, and make the pattern after random
cropping and deformation still have an adversarial effect, then we can process
the flat cloth with an adversarial pattern into any 3D clothes. The results
showed that the optimized "QR code" pattern lowered the Average Precision (AP)
of YOLOv3 by 87.7%, while the random "QR code" pattern and blank pattern
lowered the AP of YOLOv3 by 57.9% and 30.1%, respectively, in the digital
world. We then manufactured an adversarial shirt with a new material: aerogel.
Physical-world experiments showed that the adversarial "QR code" pattern
clothing lowered the AP of YOLOv3 by 64.6%, while the random "QR code" pattern
clothing and fully heat-insulated clothing lowered the AP of YOLOv3 by 28.3%
and 22.8%, respectively. We used the model ensemble technique to improve the
attack transferability to unseen models.

本文提出了一种基于红外对抗技术的服装设计方法，设计出一种反可见光的 QR 码图案，制造出一件防检测衣服，在数字世界和物理世界的实验中，分别测试了适用性和迁移性。