Saved in:
| Main Author: | Zhao, Ying |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.04340 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
MIRAGE: Model-agnostic Industrial Realistic Anomaly Generation and Evaluation for Visual Anomaly Detection
by: Hu, Jinwei, et al.
Published: (2026)
by: Hu, Jinwei, et al.
Published: (2026)
AnomalyFactory: Regard Anomaly Generation as Unsupervised Anomaly Localization
by: Zhao, Ying
Published: (2024)
by: Zhao, Ying
Published: (2024)
AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection
by: Zhou, Qihang, et al.
Published: (2023)
by: Zhou, Qihang, et al.
Published: (2023)
Component-aware Unsupervised Logical Anomaly Generation for Industrial Anomaly Detection
by: Tong, Xuan, et al.
Published: (2025)
by: Tong, Xuan, et al.
Published: (2025)
GeneralAD: Anomaly Detection Across Domains by Attending to Distorted Features
by: Sträter, Luc P. J., et al.
Published: (2024)
by: Sträter, Luc P. J., et al.
Published: (2024)
Generalization-aware Remote Sensing Change Detection via Domain-agnostic Learning
by: Zang, Qi, et al.
Published: (2025)
by: Zang, Qi, et al.
Published: (2025)
GlocalCLIP: Object-agnostic Global-Local Prompt Learning for Zero-shot Anomaly Detection
by: Ham, Jiyul, et al.
Published: (2024)
by: Ham, Jiyul, et al.
Published: (2024)
Double Helix Diffusion for Cross-Domain Anomaly Image Generation
by: Wu, Linchun, et al.
Published: (2025)
by: Wu, Linchun, et al.
Published: (2025)
Fence off Anomaly Interference: Cross-Domain Distillation for Fully Unsupervised Anomaly Detection
by: Liu, Xinyue, et al.
Published: (2025)
by: Liu, Xinyue, et al.
Published: (2025)
Semantic Visual Anomaly Detection and Reasoning in AI-Generated Images
by: Tan, Chuangchuang, et al.
Published: (2025)
by: Tan, Chuangchuang, et al.
Published: (2025)
Weakly Supervised Video Anomaly Detection with Anomaly-Connected Components and Intention Reasoning
by: Wang, Yu, et al.
Published: (2026)
by: Wang, Yu, et al.
Published: (2026)
Pseudo Anomalies Are All You Need: Diffusion-Based Generation for Weakly-Supervised Video Anomaly Detection
by: Hashimoto, Satoshi, et al.
Published: (2025)
by: Hashimoto, Satoshi, et al.
Published: (2025)
Improving Anomaly Detection with Foundation-Model Synthesis and Wavelet-Domain Attention
by: Wu, Wensheng, et al.
Published: (2026)
by: Wu, Wensheng, et al.
Published: (2026)
Unseen Visual Anomaly Generation
by: Sun, Han, et al.
Published: (2024)
by: Sun, Han, et al.
Published: (2024)
AnomalyDiffusion: Few-Shot Anomaly Image Generation with Diffusion Model
by: Hu, Teng, et al.
Published: (2023)
by: Hu, Teng, et al.
Published: (2023)
Learn Suspected Anomalies from Event Prompts for Video Anomaly Detection
by: Tao, Chenchen, et al.
Published: (2024)
by: Tao, Chenchen, et al.
Published: (2024)
Self-Supervised Learning for Detecting AI-Generated Faces as Anomalies
by: Zou, Mian, et al.
Published: (2025)
by: Zou, Mian, et al.
Published: (2025)
Noise-Informed Diffusion-Generated Image Detection with Anomaly Attention
by: Guan, Weinan, et al.
Published: (2025)
by: Guan, Weinan, et al.
Published: (2025)
ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection
by: Hu, Lei, et al.
Published: (2025)
by: Hu, Lei, et al.
Published: (2025)
A Recover-then-Discriminate Framework for Robust Anomaly Detection
by: Xing, Peng, et al.
Published: (2024)
by: Xing, Peng, et al.
Published: (2024)
Domain Adaptation of Attention Heads for Zero-shot Anomaly Detection
by: Jeong, Kiyoon, et al.
Published: (2025)
by: Jeong, Kiyoon, et al.
Published: (2025)
Cross-Domain Learning for Video Anomaly Detection with Limited Supervision
by: Jain, Yashika, et al.
Published: (2024)
by: Jain, Yashika, et al.
Published: (2024)
VADMamba++: Efficient Video Anomaly Detection via Hybrid Modeling in Grayscale Space
by: Lyu, Jihao, et al.
Published: (2026)
by: Lyu, Jihao, et al.
Published: (2026)
ASBench: Image Anomalies Synthesis Benchmark for Anomaly Detection
by: Zhang, Qunyi, et al.
Published: (2025)
by: Zhang, Qunyi, et al.
Published: (2025)
Safeguarding Generative AI Applications in Preclinical Imaging through Hybrid Anomaly Detection
by: Binda, Jakub, et al.
Published: (2025)
by: Binda, Jakub, et al.
Published: (2025)
HDM: Hybrid Diffusion Model for Unified Image Anomaly Detection
by: Weng, Zekang, et al.
Published: (2025)
by: Weng, Zekang, et al.
Published: (2025)
Exploring the Magnitude-Shape Plot Framework for Anomaly Detection in Crowded Video Scenes
by: Wang, Zuzheng, et al.
Published: (2024)
by: Wang, Zuzheng, et al.
Published: (2024)
Zero-Shot Image Anomaly Detection Using Generative Foundation Models
by: Abdi, Lemar, et al.
Published: (2025)
by: Abdi, Lemar, et al.
Published: (2025)
GenCLIP: Generalizing CLIP Prompts for Zero-shot Anomaly Detection
by: Kim, Donghyeong, et al.
Published: (2025)
by: Kim, Donghyeong, et al.
Published: (2025)
Anomalies by Synthesis: Anomaly Detection using Generative Diffusion Models for Off-Road Navigation
by: Ancha, Siddharth, et al.
Published: (2025)
by: Ancha, Siddharth, et al.
Published: (2025)
UniADC: A Unified Framework for Anomaly Detection and Classification
by: Zhang, Ximiao, et al.
Published: (2025)
by: Zhang, Ximiao, et al.
Published: (2025)
Generate Aligned Anomaly: Region-Guided Few-Shot Anomaly Image-Mask Pair Synthesis for Industrial Inspection
by: Lu, Yilin, et al.
Published: (2025)
by: Lu, Yilin, et al.
Published: (2025)
A Comprehensive Augmentation Framework for Anomaly Detection
by: Lin, Jiang, et al.
Published: (2023)
by: Lin, Jiang, et al.
Published: (2023)
Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation
by: Gui, Guan, et al.
Published: (2025)
by: Gui, Guan, et al.
Published: (2025)
ASTER: Latent Pseudo-Anomaly Generation for Unsupervised Time-Series Anomaly Detection
by: Hermary, Romain, et al.
Published: (2026)
by: Hermary, Romain, et al.
Published: (2026)
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection
by: Zhu, Jiawen, et al.
Published: (2023)
by: Zhu, Jiawen, et al.
Published: (2023)
Towards Continual Visual Anomaly Detection in the Medical Domain
by: Barusco, Manuel, et al.
Published: (2025)
by: Barusco, Manuel, et al.
Published: (2025)
GroundingAnomaly: Spatially-Grounded Diffusion for Few-Shot Anomaly Synthesis
by: Liu, Yishen, et al.
Published: (2026)
by: Liu, Yishen, et al.
Published: (2026)
A Scalable and Generalized Deep Learning Framework for Anomaly Detection in Surveillance Videos
by: Jebur, Sabah Abdulazeez, et al.
Published: (2024)
by: Jebur, Sabah Abdulazeez, et al.
Published: (2024)
AnomalyLMM: Bridging Generative Knowledge and Discriminative Retrieval for Text-Based Person Anomaly Search
by: Ju, Hao, et al.
Published: (2025)
by: Ju, Hao, et al.
Published: (2025)
Similar Items
-
MIRAGE: Model-agnostic Industrial Realistic Anomaly Generation and Evaluation for Visual Anomaly Detection
by: Hu, Jinwei, et al.
Published: (2026) -
AnomalyFactory: Regard Anomaly Generation as Unsupervised Anomaly Localization
by: Zhao, Ying
Published: (2024) -
AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection
by: Zhou, Qihang, et al.
Published: (2023) -
Component-aware Unsupervised Logical Anomaly Generation for Industrial Anomaly Detection
by: Tong, Xuan, et al.
Published: (2025) -
GeneralAD: Anomaly Detection Across Domains by Attending to Distorted Features
by: Sträter, Luc P. J., et al.
Published: (2024)