Copertina

Detecting and Corrupting Convolution-based Unlearnable Examples

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Li, Minghui, Wang, Xianlong, Yu, Zhifei, Hu, Shengshan, Zhou, Ziqi, Zhang, Longling, Zhang, Leo Yu
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Computer Vision and Pattern Recognition Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

PB-UAP: Hybrid Universal Adversarial Attack For Image Segmentation
di: Song, Yufei, et al.
Pubblicazione: (2024)

Unlearnable 3D Point Clouds: Class-wise Transformation Is All You Need
di: Wang, Xianlong, et al.
Pubblicazione: (2024)

Dual-branch Robust Unlearnable Examples
di: Wang, Xianlong, et al.
Pubblicazione: (2026)

Transferable Adversarial Facial Images for Privacy Protection
di: Li, Minghui, et al.
Pubblicazione: (2024)

T2UE: Generating Unlearnable Examples from Text Descriptions
di: Ma, Xingjun, et al.
Pubblicazione: (2025)

SegTrans: Transferable Adversarial Examples for Segmentation Models
di: Song, Yufei, et al.
Pubblicazione: (2025)

Detector Collapse: Physical-World Backdooring Object Detection to Catastrophic Overload or Blindness in Autonomous Driving
di: Zhang, Hangtao, et al.
Pubblicazione: (2024)

ADVEDM:Fine-grained Adversarial Attack against VLM-based Embodied Agents
di: Wang, Yichen, et al.
Pubblicazione: (2025)

Purify Unlearnable Examples via Rate-Constrained Variational Autoencoders
di: Yu, Yi, et al.
Pubblicazione: (2024)

Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples
di: Zhou, Ziqi, et al.
Pubblicazione: (2024)

Towards Real-World Deepfake Detection: A Diverse In-the-wild Dataset of Forgery Faces
di: Shi, Junyu, et al.
Pubblicazione: (2025)

Breaking Barriers in Physical-World Adversarial Examples: Improving Robustness and Transferability via Robust Feature
di: Wang, Yichen, et al.
Pubblicazione: (2024)

Erosion Attack for Adversarial Training to Enhance Semantic Segmentation Robustness
di: Song, Yufei, et al.
Pubblicazione: (2026)

Test-Time Backdoor Detection for Object Detection Models
di: Zhang, Hangtao, et al.
Pubblicazione: (2025)

Transferable Physical-World Adversarial Patches Against Pedestrian Detection Models
di: Yan, Shihui, et al.
Pubblicazione: (2026)

Transferable Physical-World Adversarial Patches Against Object Detection in Autonomous Driving
di: Zhu, Zihui, et al.
Pubblicazione: (2026)

NumbOD: A Spatial-Frequency Fusion Attack Against Object Detectors
di: Zhou, Ziqi, et al.
Pubblicazione: (2024)

PIP: Detecting Adversarial Examples in Large Vision-Language Models via Attention Patterns of Irrelevant Probe Questions
di: Zhang, Yudong, et al.
Pubblicazione: (2024)

Unlearnable Examples Detection via Iterative Filtering
di: Yu, Yi, et al.
Pubblicazione: (2024)

A Parameter-efficient Convolutional Approach for Weed Detection in Multispectral Aerial Imagery
di: Ramos, Leo Thomas, et al.
Pubblicazione: (2026)

DDNet: Deformable Convolution and Dense FPN for Surface Defect Detection in Recycled Books
di: Yu, Jun, et al.
Pubblicazione: (2024)

RMem: Restricted Memory Banks Improve Video Object Segmentation
di: Zhou, Junbao, et al.
Pubblicazione: (2024)

DarkHash: A Data-Free Backdoor Attack Against Deep Hashing
di: Zhou, Ziqi, et al.
Pubblicazione: (2025)

ECLIPSE: Expunging Clean-label Indiscriminate Poisons via Sparse Diffusion Purification
di: Wang, Xianlong, et al.
Pubblicazione: (2024)

Example-Based Object Detection
di: Sun, ZhiXin
Pubblicazione: (2026)

DarkSAM: Fooling Segment Anything Model to Segment Nothing
di: Zhou, Ziqi, et al.
Pubblicazione: (2024)

Unlearnable Examples for Diffusion Models: Protect Data from Unauthorized Exploitation
di: Zhao, Zhengyue, et al.
Pubblicazione: (2023)

Semantic Deep Hiding for Robust Unlearnable Examples
di: Meng, Ruohan, et al.
Pubblicazione: (2024)

TextHawk2: A Large Vision-Language Model Excels in Bilingual OCR and Grounding with 16x Fewer Tokens
di: Yu, Ya-Qi, et al.
Pubblicazione: (2024)

UnlearnShield: Shielding Forgotten Privacy against Unlearning Inversion
di: Xue, Lulu, et al.
Pubblicazione: (2026)

MultiCorrupt: A Multi-Modal Robustness Dataset and Benchmark of LiDAR-Camera Fusion for 3D Object Detection
di: Beemelmanns, Till, et al.
Pubblicazione: (2024)

CLIPDrag: Combining Text-based and Drag-based Instructions for Image Editing
di: Jiang, Ziqi, et al.
Pubblicazione: (2024)

AEMIM: Adversarial Examples Meet Masked Image Modeling
di: Xiang, Wenzhao, et al.
Pubblicazione: (2024)

Fighting Fire with Fire (F3): A Training-free and Efficient Visual Adversarial Example Purification Method in LVLMs
di: Zhang, Yudong, et al.
Pubblicazione: (2025)

PoseBench: Benchmarking the Robustness of Pose Estimation Models under Corruptions
di: Ma, Sihan, et al.
Pubblicazione: (2024)

Dense Cross-Connected Ensemble Convolutional Neural Networks for Enhanced Model Robustness
di: Wang, Longwei, et al.
Pubblicazione: (2024)

DynamicPAE: Generating Scene-Aware Physical Adversarial Examples in Real-Time
di: Hu, Jin, et al.
Pubblicazione: (2024)

Integrating Object Interaction Self-Attention and GAN-Based Debiasing for Visual Question Answering
di: Li, Zhifei, et al.
Pubblicazione: (2025)

Enhancing Sampling Protocol for Point Cloud Classification Against Corruptions
di: Li, Chongshou, et al.
Pubblicazione: (2024)

Unlearnable Examples Give a False Sense of Data Privacy: Understanding and Relearning
di: Dang, Pucheng, et al.
Pubblicazione: (2023)