Saved in:
| Main Authors: | Heo, Jaehyuk, Kang, Pilsung |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2508.02477 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Domain Adaptation of Attention Heads for Zero-shot Anomaly Detection
by: Jeong, Kiyoon, et al.
Published: (2025)
by: Jeong, Kiyoon, et al.
Published: (2025)
Avoid Wasted Annotation Costs in Open-set Active Learning with Pre-trained Vision-Language Model
by: Heo, Jaehyuk, et al.
Published: (2024)
by: Heo, Jaehyuk, et al.
Published: (2024)
Learning Multi-view Multi-class Anomaly Detection
by: Yu, Qianzi, et al.
Published: (2025)
by: Yu, Qianzi, et al.
Published: (2025)
Prior Normality Prompt Transformer for Multi-class Industrial Image Anomaly Detection
by: Yao, Haiming, et al.
Published: (2024)
by: Yao, Haiming, et al.
Published: (2024)
Center-aware Residual Anomaly Synthesis for Multi-class Industrial Anomaly Detection
by: Chen, Qiyu, et al.
Published: (2025)
by: Chen, Qiyu, et al.
Published: (2025)
Collaborative Reconstruction and Repair for Multi-class Industrial Anomaly Detection
by: Wang, Qishan, et al.
Published: (2025)
by: Wang, Qishan, et al.
Published: (2025)
Pyramid-based Mamba Multi-class Unsupervised Anomaly Detection
by: Iqbal, Nasar, et al.
Published: (2025)
by: Iqbal, Nasar, et al.
Published: (2025)
Technical Report of NICE Challenge at CVPR 2024: Caption Re-ranking Evaluation Using Ensembled CLIP and Consensus Scores
by: Jeong, Kiyoon, et al.
Published: (2024)
by: Jeong, Kiyoon, et al.
Published: (2024)
Learning to Detect Multi-class Anomalies with Just One Normal Image Prompt
by: Gao, Bin-Bin
Published: (2025)
by: Gao, Bin-Bin
Published: (2025)
A Comprehensive Library for Benchmarking Multi-class Visual Anomaly Detection
by: Zhang, Jiangning, et al.
Published: (2024)
by: Zhang, Jiangning, et al.
Published: (2024)
Learning Unified Reference Representation for Unsupervised Multi-class Anomaly Detection
by: He, Liren, et al.
Published: (2024)
by: He, Liren, et al.
Published: (2024)
Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection
by: Zhang, Jiangning, et al.
Published: (2023)
by: Zhang, Jiangning, et al.
Published: (2023)
Toward Multi-class Anomaly Detection: Exploring Class-aware Unified Model against Inter-class Interference
by: Jiang, Xi, et al.
Published: (2024)
by: Jiang, Xi, et al.
Published: (2024)
Anomaly Detection for Industrial Applications, Its Challenges, Solutions, and Future Directions: A Review
by: Alzarooni, Abdelrahman, et al.
Published: (2025)
by: Alzarooni, Abdelrahman, et al.
Published: (2025)
A Prototype-Based Neural Network for Image Anomaly Detection and Localization
by: Huang, Chao, et al.
Published: (2023)
by: Huang, Chao, et al.
Published: (2023)
Omni-AD: Learning to Reconstruct Global and Local Features for Multi-class Anomaly Detection
by: Quan, Jiajie, et al.
Published: (2025)
by: Quan, Jiajie, et al.
Published: (2025)
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection
by: He, Haoyang, et al.
Published: (2024)
by: He, Haoyang, et al.
Published: (2024)
RAD: A Comprehensive Dataset for Benchmarking the Robustness of Image Anomaly Detection
by: Cheng, Yuqi, et al.
Published: (2024)
by: Cheng, Yuqi, et al.
Published: (2024)
ASBench: Image Anomalies Synthesis Benchmark for Anomaly Detection
by: Zhang, Qunyi, et al.
Published: (2025)
by: Zhang, Qunyi, et al.
Published: (2025)
Pro-AD: Learning Comprehensive Prototypes with Prototype-based Constraint for Multi-class Unsupervised Anomaly Detection
by: Zhou, Ziqing, et al.
Published: (2025)
by: Zhou, Ziqing, et al.
Published: (2025)
Learning Feature Inversion for Multi-class Anomaly Detection under General-purpose COCO-AD Benchmark
by: Zhang, Jiangning, et al.
Published: (2024)
by: Zhang, Jiangning, et al.
Published: (2024)
ProtoAnomalyNCD: Prototype Learning for Multi-class Novel Anomaly Discovery in Industrial Scenarios
by: Zhao, Botong, et al.
Published: (2025)
by: Zhao, Botong, et al.
Published: (2025)
Attention Fusion Reverse Distillation for Multi-Lighting Image Anomaly Detection
by: Zhang, Yiheng, et al.
Published: (2024)
by: Zhang, Yiheng, et al.
Published: (2024)
ROADS: Robust Prompt-driven Multi-Class Anomaly Detection under Domain Shift
by: Kashiani, Hossein, et al.
Published: (2024)
by: Kashiani, Hossein, et al.
Published: (2024)
Anomaly Detection by Effectively Leveraging Synthetic Images
by: Kang, Sungho, et al.
Published: (2025)
by: Kang, Sungho, et al.
Published: (2025)
FakeChain: Exposing Shallow Cues in Multi-Step Deepfake Detection
by: Heo, Minji, et al.
Published: (2025)
by: Heo, Minji, et al.
Published: (2025)
Efficient Test-Time Optimization for Depth Completion via Low-Rank Decoder Adaptation
by: Seo, Minseok, et al.
Published: (2026)
by: Seo, Minseok, et al.
Published: (2026)
A Recover-then-Discriminate Framework for Robust Anomaly Detection
by: Xing, Peng, et al.
Published: (2024)
by: Xing, Peng, et al.
Published: (2024)
Memory-Distilled Selection for Noise-Robust Anomaly Detection
by: Safarov, Sirojbek, et al.
Published: (2026)
by: Safarov, Sirojbek, et al.
Published: (2026)
SD-MAD: Sign-Driven Few-shot Multi-Anomaly Detection in Medical Images
by: Guo, Kaiyu, et al.
Published: (2025)
by: Guo, Kaiyu, et al.
Published: (2025)
Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection
by: Xu, Muhao, et al.
Published: (2025)
by: Xu, Muhao, et al.
Published: (2025)
HomographyAD: Deep Anomaly Detection Using Self Homography Learning
by: Seok, Jongyub, et al.
Published: (2025)
by: Seok, Jongyub, et al.
Published: (2025)
I$^2$-SLAM: Inverting Imaging Process for Robust Photorealistic Dense SLAM
by: Bae, Gwangtak, et al.
Published: (2024)
by: Bae, Gwangtak, et al.
Published: (2024)
Hyperspectral Trajectory Image for Multi-Month Trajectory Anomaly Detection
by: Rahman, Md Awsafur, et al.
Published: (2026)
by: Rahman, Md Awsafur, et al.
Published: (2026)
RITUAL: Random Image Transformations as a Universal Anti-hallucination Lever in Large Vision Language Models
by: Woo, Sangmin, et al.
Published: (2024)
by: Woo, Sangmin, et al.
Published: (2024)
Mitigating Spurious Negative Pairs for Robust Industrial Anomaly Detection
by: Mirzaei, Hossein, et al.
Published: (2025)
by: Mirzaei, Hossein, et al.
Published: (2025)
CNC: Cross-modal Normality Constraint for Unsupervised Multi-class Anomaly Detection
by: Wang, Xiaolei, et al.
Published: (2024)
by: Wang, Xiaolei, et al.
Published: (2024)
Towards High-Resolution Industrial Image Anomaly Detection
by: Zhang, Ximiao, et al.
Published: (2025)
by: Zhang, Ximiao, et al.
Published: (2025)
Deep Industrial Image Anomaly Detection: A Survey
by: Liu, Jiaqi, et al.
Published: (2023)
by: Liu, Jiaqi, et al.
Published: (2023)
Practical Manipulation Model for Robust Deepfake Detection
by: Hopf, Benedikt, et al.
Published: (2025)
by: Hopf, Benedikt, et al.
Published: (2025)
Similar Items
-
Domain Adaptation of Attention Heads for Zero-shot Anomaly Detection
by: Jeong, Kiyoon, et al.
Published: (2025) -
Avoid Wasted Annotation Costs in Open-set Active Learning with Pre-trained Vision-Language Model
by: Heo, Jaehyuk, et al.
Published: (2024) -
Learning Multi-view Multi-class Anomaly Detection
by: Yu, Qianzi, et al.
Published: (2025) -
Prior Normality Prompt Transformer for Multi-class Industrial Image Anomaly Detection
by: Yao, Haiming, et al.
Published: (2024) -
Center-aware Residual Anomaly Synthesis for Multi-class Industrial Anomaly Detection
by: Chen, Qiyu, et al.
Published: (2025)