DePatch: Towards Robust Adversarial Patch for Evading Person Detectors in the Real World
Fuente:
arXiv
Saved in:
| Main Authors: | Cheng, Jikang, Zhang, Ying, Wang, Zhongyuan, Qin, Zou, Li, Chen |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Can We Leave Deepfake Data Behind in Training Deepfake Detector?
by: Cheng, Jikang, et al.
Published: (2024)
by: Cheng, Jikang, et al.
Published: (2024)
Higher-Order Adversarial Patches for Real-Time Object Detectors
by: Bayer, Jens, et al.
Published: (2026)
by: Bayer, Jens, et al.
Published: (2026)
PAD: Patch-Agnostic Defense against Adversarial Patch Attacks
by: Jing, Lihua, et al.
Published: (2024)
by: Jing, Lihua, et al.
Published: (2024)
ED$^4$: Explicit Data-level Debiasing for Deepfake Detection
by: Cheng, Jikang, et al.
Published: (2024)
by: Cheng, Jikang, et al.
Published: (2024)
IDRetracor: Towards Visual Forensics Against Malicious Face Swapping
by: Cheng, Jikang, et al.
Published: (2024)
by: Cheng, Jikang, et al.
Published: (2024)
Stacking Brick by Brick: Aligned Feature Isolation for Incremental Face Forgery Detection
by: Cheng, Jikang, et al.
Published: (2024)
by: Cheng, Jikang, et al.
Published: (2024)
MVPatch: More Vivid Patch for Adversarial Camouflaged Attacks on Object Detectors in the Physical World
by: Zhou, Zheng, et al.
Published: (2023)
by: Zhou, Zheng, et al.
Published: (2023)
Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?
by: Fu, Yonggan, et al.
Published: (2022)
by: Fu, Yonggan, et al.
Published: (2022)
Adversarial 3D Virtual Patches using Integrated Gradients
by: You, Chengzeng, et al.
Published: (2024)
by: You, Chengzeng, et al.
Published: (2024)
Towards Physically Realizable Adversarial Attenuation Patch against SAR Object Detection
by: Zhang, Yiming, et al.
Published: (2026)
by: Zhang, Yiming, et al.
Published: (2026)
BadPatch: Diffusion-Based Generation of Physical Adversarial Patches
by: Wang, Zhixiang, et al.
Published: (2024)
by: Wang, Zhixiang, et al.
Published: (2024)
DisPatch: Disarming Adversarial Patches in Object Detection with Diffusion Models
by: Ma, Jin, et al.
Published: (2025)
by: Ma, Jin, et al.
Published: (2025)
The Unseen Adversaries: Robust and Generalized Defense Against Adversarial Patches
by: Kumar, Vishesh, et al.
Published: (2026)
by: Kumar, Vishesh, et al.
Published: (2026)
A Sanity Check for Multi-In-Domain Face Forgery Detection in the Real World
by: Cheng, Jikang, et al.
Published: (2025)
by: Cheng, Jikang, et al.
Published: (2025)
Transferable Physical-World Adversarial Patches Against Object Detection in Autonomous Driving
by: Zhu, Zihui, et al.
Published: (2026)
by: Zhu, Zihui, et al.
Published: (2026)
Transferable Physical-World Adversarial Patches Against Pedestrian Detection Models
by: Yan, Shihui, et al.
Published: (2026)
by: Yan, Shihui, et al.
Published: (2026)
ID-Patch: Robust ID Association for Group Photo Personalization
by: Zhang, Yimeng, et al.
Published: (2024)
by: Zhang, Yimeng, et al.
Published: (2024)
Prompt-Guided Environmentally Consistent Adversarial Patch
by: Li, Chaoqun, et al.
Published: (2024)
by: Li, Chaoqun, et al.
Published: (2024)
AdvLogo: Adversarial Patch Attack against Object Detectors based on Diffusion Models
by: Miao, Boming, et al.
Published: (2024)
by: Miao, Boming, et al.
Published: (2024)
Traversing the Subspace of Adversarial Patches
by: Bayer, Jens, et al.
Published: (2024)
by: Bayer, Jens, et al.
Published: (2024)
Robust Physical Adversarial Patches Using Dynamically Optimized Clusters
by: Bagley, Harrison, et al.
Published: (2025)
by: Bagley, Harrison, et al.
Published: (2025)
AngleRoCL: Angle-Robust Concept Learning for Physically View-Invariant T2I Adversarial Patches
by: Ji, Wenjun, et al.
Published: (2025)
by: Ji, Wenjun, et al.
Published: (2025)
Fool the Stoplight: Realistic Adversarial Patch Attacks on Traffic Light Detectors
by: Pavlitska, Svetlana, et al.
Published: (2025)
by: Pavlitska, Svetlana, et al.
Published: (2025)
Take Fake as Real: Realistic-like Robust Black-box Adversarial Attack to Evade AIGC Detection
by: Xie, Caiyun, et al.
Published: (2024)
by: Xie, Caiyun, et al.
Published: (2024)
API: Empowering Generalizable Real-World Image Dehazing via Adaptive Patch Importance Learning
by: Zhu, Chen, et al.
Published: (2026)
by: Zhu, Chen, et al.
Published: (2026)
PatchCURE: Improving Certifiable Robustness, Model Utility, and Computation Efficiency of Adversarial Patch Defenses
by: Xiang, Chong, et al.
Published: (2023)
by: Xiang, Chong, et al.
Published: (2023)
Towards Robust Semantic Segmentation against Patch-based Attack via Attention Refinement
by: Yuan, Zheng, et al.
Published: (2024)
by: Yuan, Zheng, et al.
Published: (2024)
TPatch: A Triggered Physical Adversarial Patch
by: Zhu, Wenjun, et al.
Published: (2023)
by: Zhu, Wenjun, et al.
Published: (2023)
Revisiting Adversarial Patch Defenses on Object Detectors: Unified Evaluation, Large-Scale Dataset, and New Insights
by: Zheng, Junhao, et al.
Published: (2025)
by: Zheng, Junhao, et al.
Published: (2025)
Fight Fire with Fire: Combating Adversarial Patch Attacks using Pattern-randomized Defensive Patches
by: Feng, Jianan, et al.
Published: (2023)
by: Feng, Jianan, et al.
Published: (2023)
All Patches Matter, More Patches Better: Enhance AI-Generated Image Detection via Panoptic Patch Learning
by: Yang, Zheng, et al.
Published: (2025)
by: Yang, Zheng, et al.
Published: (2025)
PatchDPO: Patch-level DPO for Finetuning-free Personalized Image Generation
by: Huang, Qihan, et al.
Published: (2024)
by: Huang, Qihan, et al.
Published: (2024)
PhysPatch: A Physically Realizable and Transferable Adversarial Patch Attack for Multimodal Large Language Models-based Autonomous Driving Systems
by: Guo, Qi, et al.
Published: (2025)
by: Guo, Qi, et al.
Published: (2025)
AdvReal: Physical Adversarial Patch Generation Framework for Security Evaluation of Object Detection Systems
by: Huang, Yuanhao, et al.
Published: (2025)
by: Huang, Yuanhao, et al.
Published: (2025)
Divide and Conquer: Reliable Multi-View Evidential Learning for Deepfake Detection
by: Kang, Xiaolu, et al.
Published: (2026)
by: Kang, Xiaolu, et al.
Published: (2026)
SuperPatchMatch: an Algorithm for Robust Correspondences using Superpixel Patches
by: Giraud, Rémi, et al.
Published: (2019)
by: Giraud, Rémi, et al.
Published: (2019)
Adversarial Robustness of AI-Generated Image Detectors in the Real World
by: Mavali, Sina, et al.
Published: (2024)
by: Mavali, Sina, et al.
Published: (2024)
Physical Adversarial Clothing Evades Visible-Thermal Detectors via Non-Overlapping RGB-T Pattern
by: Zhu, Xiaopei, et al.
Published: (2026)
by: Zhu, Xiaopei, et al.
Published: (2026)
CapGen:An Environment-Adaptive Generator of Adversarial Patches
by: Li, Chaoqun, et al.
Published: (2024)
by: Li, Chaoqun, et al.
Published: (2024)
Adversarial Patch for 3D Local Feature Extractor
by: Pao, Yu Wen, et al.
Published: (2024)
by: Pao, Yu Wen, et al.
Published: (2024)
Similar Items
-
Can We Leave Deepfake Data Behind in Training Deepfake Detector?
by: Cheng, Jikang, et al.
Published: (2024) -
Higher-Order Adversarial Patches for Real-Time Object Detectors
by: Bayer, Jens, et al.
Published: (2026) -
PAD: Patch-Agnostic Defense against Adversarial Patch Attacks
by: Jing, Lihua, et al.
Published: (2024) -
ED$^4$: Explicit Data-level Debiasing for Deepfake Detection
by: Cheng, Jikang, et al.
Published: (2024) -
IDRetracor: Towards Visual Forensics Against Malicious Face Swapping
by: Cheng, Jikang, et al.
Published: (2024)