Imagen de Portada

KKA: Improving Vision Anomaly Detection through Anomaly-related Knowledge from Large Language Models

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Chen, Dong, Hu, Zhengqing, Fan, Peiguang, Zhuang, Yueting, Li, Yafei, Liu, Qidong, Jiang, Xiaoheng, Xu, Mingliang
Formato:	Preprint
Publicado:	2025
Materias:	Computer Vision and Pattern Recognition Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

GMFVAD: Using Grained Multi-modal Feature to Improve Video Anomaly Detection
por: Dai, Guangyu, et al.
Publicado: (2025)

Few-Shot Object Detection with Sparse Context Transformers
por: Mei, Jie, et al.
Publicado: (2024)

Vision-Language Models Assisted Unsupervised Video Anomaly Detection
por: Jiang, Yalong, et al.
Publicado: (2024)

Topo-R1: Detecting Topological Anomalies via Vision-Language Models
por: Xu, Meilong, et al.
Publicado: (2026)

Exploring Large Vision-Language Models for Robust and Efficient Industrial Anomaly Detection
por: Qian, Kun, et al.
Publicado: (2024)

VL4AD: Vision-Language Models Improve Pixel-wise Anomaly Detection
por: Zhong, Liangyu, et al.
Publicado: (2024)

Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection?
por: Chen, Zhiling, et al.
Publicado: (2025)

Robust Modality-incomplete Anomaly Detection: A Modality-instructive Framework with Benchmark
por: Miao, Bingchen, et al.
Publicado: (2024)

Anomaly-Aware Vision-Language Adapters for Zero-Shot Anomaly Detection
por: Aqeel, Muhammad, et al.
Publicado: (2026)

Normal and Abnormal Pathology Knowledge-Augmented Vision-Language Model for Anomaly Detection in Pathology Images
por: Song, Jinsol, et al.
Publicado: (2025)

Towards Fine-Grained Vision-Language Alignment for Few-Shot Anomaly Detection
por: Fan, Yuanting, et al.
Publicado: (2025)

PatchGuard: Adversarially Robust Anomaly Detection and Localization through Vision Transformers and Pseudo Anomalies
por: Nafez, Mojtaba, et al.
Publicado: (2025)

From Heads to Neurons: Causal Attribution and Steering in Multi-Task Vision-Language Models
por: Wang, Qidong, et al.
Publicado: (2026)

Myriad: Large Multimodal Model by Applying Vision Experts for Industrial Anomaly Detection
por: Li, Yuanze, et al.
Publicado: (2023)

Chain-of-Anomaly Thoughts with Large Vision-Language Models
por: Domingos, Pedro, et al.
Publicado: (2025)

IAD-GPT: Advancing Visual Knowledge in Multimodal Large Language Model for Industrial Anomaly Detection
por: Li, Zewen, et al.
Publicado: (2025)

Distilling Aggregated Knowledge for Weakly-Supervised Video Anomaly Detection
por: Dalvi, Jash, et al.
Publicado: (2024)

ASBench: Image Anomalies Synthesis Benchmark for Anomaly Detection
por: Zhang, Qunyi, et al.
Publicado: (2025)

Self-Navigated Residual Mamba for Universal Industrial Anomaly Detection
por: Li, Hanxi, et al.
Publicado: (2025)

Towards Training-free Anomaly Detection with Vision and Language Foundation Models
por: Zhang, Jinjin, et al.
Publicado: (2025)

Anomaly Detection by Adapting a pre-trained Vision Language Model
por: Cai, Yuxuan, et al.
Publicado: (2024)

Enhancing Anomaly Detection Generalization through Knowledge Exposure: The Dual Effects of Augmentation
por: Anvari, Mohammad Akhavan, et al.
Publicado: (2024)

VisualAD: Language-Free Zero-Shot Anomaly Detection via Vision Transformer
por: Hou, Yanning, et al.
Publicado: (2026)

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

Video Anomaly Detection and Explanation via Large Language Models
por: Lv, Hui, et al.
Publicado: (2024)

FADE: Few-shot/zero-shot Anomaly Detection Engine using Large Vision-Language Model
por: Li, Yuanwei, et al.
Publicado: (2024)

AnomalyLMM: Bridging Generative Knowledge and Discriminative Retrieval for Text-Based Person Anomaly Search
por: Ju, Hao, et al.
Publicado: (2025)

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

Unveiling Context-Related Anomalies: Knowledge Graph Empowered Decoupling of Scene and Action for Human-Related Video Anomaly Detection
por: Chen, Chenglizhao, et al.
Publicado: (2024)

PA-CLIP: Enhancing Zero-Shot Anomaly Detection through Pseudo-Anomaly Awareness
por: Pan, Yurui, et al.
Publicado: (2025)

One Language-Free Foundation Model Is Enough for Universal Vision Anomaly Detection
por: Gao, Bin-Bin, et al.
Publicado: (2026)

VLMDiff: Leveraging Vision-Language Models for Multi-Class Anomaly Detection with Diffusion
por: Hicsonmez, Samet, et al.
Publicado: (2025)

Hyperspectral Anomaly Detection with Self-Supervised Anomaly Prior
por: Liu, Yidan, et al.
Publicado: (2024)

Seeing Is Believing? A Benchmark for Multimodal Large Language Models on Visual Illusions and Anomalies
por: Hou, Wenjin, et al.
Publicado: (2026)

Harnessing Large Language Models for Training-free Video Anomaly Detection
por: Zanella, Luca, et al.
Publicado: (2024)

Follow the Rules: Reasoning for Video Anomaly Detection with Large Language Models
por: Yang, Yuchen, et al.
Publicado: (2024)

AnomalyXFusion: Multi-modal Anomaly Synthesis with Diffusion
por: Hu, Jie, et al.
Publicado: (2024)

MANTA: A Large-Scale Multi-View and Visual-Text Anomaly Detection Dataset for Tiny Objects
por: Fan, Lei, et al.
Publicado: (2024)

Improved Anomaly Detection through Conditional Latent Space VAE Ensembles
por: Åström, Oskar, et al.
Publicado: (2024)

Vision-Language Feature Alignment for Road Anomaly Segmentation
por: He, Zhuolin, et al.
Publicado: (2026)