Cover Image

Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly Detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tao, Fenfang, Xie, Guo-Sen, Zhao, Fang, Shu, Xiangbo
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MVP-Shot: Multi-Velocity Progressive-Alignment Framework for Few-Shot Action Recognition
by: Qu, Hongyu, et al.
Published: (2024)

PromptAD: Learning Prompts with only Normal Samples for Few-Shot Anomaly Detection
by: Li, Xiaofan, et al.
Published: (2024)

SAM-Aware Graph Prompt Reasoning Network for Cross-Domain Few-Shot Segmentation
by: Peng, Shi-Feng, et al.
Published: (2024)

Transformer Based Self-Context Aware Prediction for Few-Shot Anomaly Detection in Videos
by: Pillai, Gargi V., et al.
Published: (2025)

AFANet: Adaptive Frequency-Aware Network for Weakly-Supervised Few-Shot Semantic Segmentation
by: Ma, Jiaqi, et al.
Published: (2024)

Bidirectional Multimodal Prompt Learning with Scale-Aware Training for Few-Shot Multi-Class Anomaly Detection
by: Lee, Yujin, et al.
Published: (2024)

Prototypical Learning Guided Context-Aware Segmentation Network for Few-Shot Anomaly Detection
by: Jiang, Yuxin, et al.
Published: (2025)

ABounD: Adversarial Boundary-Driven Few-Shot Learning for Multi-Class Anomaly Detection
by: Deng, Runzhi, et al.
Published: (2025)

Bayesian Prompt Flow Learning for Zero-Shot Anomaly Detection
by: Qu, Zhen, et al.
Published: (2025)

Cluster-Aware Prompt Ensemble Learning for Few-Shot Vision-Language Model Adaptation
by: Chen, Zhi, et al.
Published: (2025)

Through the Looking Glass: A Dual Perspective on Weakly-Supervised Few-Shot Segmentation
by: Ma, Jiaqi, et al.
Published: (2025)

Attack-Augmentation Mixing-Contrastive Skeletal Representation Learning
by: Xu, Binqian, et al.
Published: (2023)

Spatio-temporal Decoupled Knowledge Compensator for Few-Shot Action Recognition
by: Qu, Hongyu, et al.
Published: (2026)

Dual Distillation for Few-Shot Anomaly Detection
by: Dong, Le, et al.
Published: (2026)

Few-Shot Anomaly Detection via Category-Agnostic Registration Learning
by: Huang, Chaoqin, et al.
Published: (2024)

Hypergraph-Enhanced Training-Free and Language-Free Few-Shot Anomaly Detection
by: Xie, Guohuan, et al.
Published: (2026)

AnomalySD: Few-Shot Multi-Class Anomaly Detection with Stable Diffusion Model
by: Yan, Zhenyu, et al.
Published: (2024)

Learn Suspected Anomalies from Event Prompts for Video Anomaly Detection
by: Tao, Chenchen, et al.
Published: (2024)

GATE-AD: Graph Attention Network Encoding For Few-Shot Industrial Visual Anomaly Detection
by: Psiris, Aggelos, et al.
Published: (2026)

Background Prompt for Few-Shot Out-of-Distribution Detection
by: Cai, Songyue, et al.
Published: (2025)

IADGPT: Unified LVLM for Few-Shot Industrial Anomaly Detection, Localization, and Reasoning via In-Context Learning
by: Zhao, Mengyang, et al.
Published: (2025)

Beyond Normal References: Discriminative Few-Shot Anomaly Detection
by: Wang, Huan, et al.
Published: (2026)

AdaFPP: Adapt-Focused Bi-Propagating Prototype Learning for Panoramic Activity Recognition
by: Cao, Meiqi, et al.
Published: (2024)

Commonality in Few: Few-Shot Multimodal Anomaly Detection via Hypergraph-Enhanced Memory
by: Lin, Yuxuan, et al.
Published: (2025)

SpatialFormer: Semantic and Target Aware Attentions for Few-Shot Learning
by: Lai, Jinxiang, et al.
Published: (2023)

AnomalyAgent: Training-Free Agentic Models for Zero-/Few-Shot Anomaly Detection
by: Zhang, Yi, et al.
Published: (2026)

DevPrompt: Deviation-Based Prompt Learning for One-Normal ShotImage Anomaly Detection
by: Poudineh, Morteza, et al.
Published: (2026)

Visual-Semantic Graph Matching Net for Zero-Shot Learning
by: Duan, Bowen, et al.
Published: (2024)

Local-Prompt: Extensible Local Prompts for Few-Shot Out-of-Distribution Detection
by: Zeng, Fanhu, et al.
Published: (2024)

LAD-Reasoner: Tiny Multimodal Models are Good Reasoners for Logical Anomaly Detection
by: Li, Weijia, et al.
Published: (2025)

CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning
by: Liu, Chengyan, et al.
Published: (2024)

GroundingAnomaly: Spatially-Grounded Diffusion for Few-Shot Anomaly Synthesis
by: Liu, Yishen, et al.
Published: (2026)

COFT-AD: COntrastive Fine-Tuning for Few-Shot Anomaly Detection
by: Liao, Jingyi, et al.
Published: (2024)

Multi-Scale Memory Comparison for Zero-/Few-Shot Anomaly Detection
by: Huang, Chaoqin, et al.
Published: (2023)

HAAF: Hierarchical Adaptation and Alignment of Foundation Models for Few-Shot Pathology Anomaly Detection
by: Yang, Chunze, et al.
Published: (2026)

Generate Aligned Anomaly: Region-Guided Few-Shot Anomaly Image-Mask Pair Synthesis for Industrial Inspection
by: Lu, Yilin, et al.
Published: (2025)

Zero-Shot Anomaly Detection with Dual-Branch Prompt Selection
by: Wang, Zihan, et al.
Published: (2025)

MAGIC: Few-Shot Mask-Guided Anomaly Inpainting with Prompt Perturbation, Spatially Adaptive Guidance, and Context Awareness
by: Choi, JaeHyuck, et al.
Published: (2025)

Toward Generalist Anomaly Detection via In-context Residual Learning with Few-shot Sample Prompts
by: Zhu, Jiawen, et al.
Published: (2024)

Crane: Context-Guided Prompt Learning and Attention Refinement for Zero-Shot Anomaly Detection
by: Salehi, Alireza, et al.
Published: (2025)