Xiaopei Zhu

Orcid: 0000-0001-8971-6475

According to our database1, Xiaopei Zhu authored at least 13 papers between 2021 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Physical Adversarial Clothing Evades Visible-Thermal Detectors via Non-Overlapping RGB-T Pattern.
CoRR, May, 2026

Crafting Physical Adversarial Examples by Combining Differentiable and Physically Based Renders.
IEEE CAA J. Autom. Sinica, March, 2026

2025
Physical Adversarial Examples for Person Detectors in Thermal Images Based on 3D Modeling.
IEEE Trans. Pattern Anal. Mach. Intell., October, 2025

A Single Set of Adversarial Clothes Breaks Multiple Defense Methods in the Physical World.
CoRR, October, 2025

2024
Hiding from thermal imaging pedestrian detectors in the physical world.
Neurocomputing, January, 2024

Natural Language Induced Adversarial Images.
CoRR, 2024

Natural Language Induced Adversarial Images.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

Infrared Adversarial Car Stickers.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Hiding from infrared detectors in real world with adversarial clothes.
Appl. Intell., December, 2023

Physically Realizable Natural-Looking Clothing Textures Evade Person Detectors via 3D Modeling.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Infrared Invisible Clothing: Hiding from Infrared Detectors at Multiple Angles in Real World.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Adversarial Texture for Fooling Person Detectors in the Physical World.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Fooling Thermal Infrared Pedestrian Detectors in Real World Using Small Bulbs.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021


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