No Need For Real Anomaly: MLLM Empowered Zero-Shot Video Anomaly Detection
Fuente:
arXiv
Guardado en:
| Autores principales: | Dai, Zunkai, Li, Ke, Liu, Jiajia, Yang, Jie, Qiao, Yuanyuan |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
ACD-CLIP: Decoupling Representation and Dynamic Fusion for Zero-Shot Anomaly Detection
por: Ma, Ke, et al.
Publicado: (2025)
por: Ma, Ke, et al.
Publicado: (2025)
Anomaly-Aware Vision-Language Adapters for Zero-Shot Anomaly Detection
por: Aqeel, Muhammad, et al.
Publicado: (2026)
por: Aqeel, Muhammad, et al.
Publicado: (2026)
SSVP: Synergistic Semantic-Visual Prompting for Industrial Zero-Shot Anomaly Detection
por: Fu, Chenhao, et al.
Publicado: (2026)
por: Fu, Chenhao, et al.
Publicado: (2026)
ViP$^2$-CLIP: Visual-Perception Prompting with Unified Alignment for Zero-Shot Anomaly Detection
por: Yang, Ziteng, et al.
Publicado: (2025)
por: Yang, Ziteng, et al.
Publicado: (2025)
Rethinking Metrics and Benchmarks of Video Anomaly Detection
por: Liu, Zihao, et al.
Publicado: (2025)
por: Liu, Zihao, et al.
Publicado: (2025)
Towards Video Anomaly Retrieval from Video Anomaly Detection: New Benchmarks and Model
por: Wu, Peng, et al.
Publicado: (2023)
por: Wu, Peng, et al.
Publicado: (2023)
FB-CLIP: Fine-Grained Zero-Shot Anomaly Detection with Foreground-Background Disentanglement
por: Hu, Ming, et al.
Publicado: (2026)
por: Hu, Ming, et al.
Publicado: (2026)
ClipSAM: CLIP and SAM Collaboration for Zero-Shot Anomaly Segmentation
por: Li, Shengze, et al.
Publicado: (2024)
por: Li, Shengze, et al.
Publicado: (2024)
AA-CLIP: Enhancing Zero-shot Anomaly Detection via Anomaly-Aware CLIP
por: Ma, Wenxin, et al.
Publicado: (2025)
por: Ma, Wenxin, et al.
Publicado: (2025)
Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation
por: Gui, Guan, et al.
Publicado: (2025)
por: Gui, Guan, et al.
Publicado: (2025)
AnomalySD: Few-Shot Multi-Class Anomaly Detection with Stable Diffusion Model
por: Yan, Zhenyu, et al.
Publicado: (2024)
por: Yan, Zhenyu, et al.
Publicado: (2024)
Are Multimodal LLMs Ready for Surveillance? A Reality Check on Zero-Shot Anomaly Detection in the Wild
por: Yao, Shanle, et al.
Publicado: (2026)
por: Yao, Shanle, et al.
Publicado: (2026)
Dynamic Distinction Learning: Adaptive Pseudo Anomalies for Video Anomaly Detection
por: Lappas, Demetris, et al.
Publicado: (2024)
por: Lappas, Demetris, et al.
Publicado: (2024)
Leveraging MLLM Embeddings and Attribute Smoothing for Compositional Zero-Shot Learning
por: Yan, Xudong, et al.
Publicado: (2024)
por: Yan, Xudong, et al.
Publicado: (2024)
Investigating the Semantic Robustness of CLIP-based Zero-Shot Anomaly Segmentation
por: Stangl, Kevin, et al.
Publicado: (2024)
por: Stangl, Kevin, et al.
Publicado: (2024)
Zero-Shot Industrial Anomaly Segmentation with Image-Aware Prompt Generation
por: Park, SoYoung, et al.
Publicado: (2025)
por: Park, SoYoung, et al.
Publicado: (2025)
Zero-to-Hero: Zero-Shot Initialization Empowering Reference-Based Video Appearance Editing
por: Su, Tongtong, et al.
Publicado: (2025)
por: Su, Tongtong, et al.
Publicado: (2025)
Networking Systems for Video Anomaly Detection: A Tutorial and Survey
por: Liu, Jing, et al.
Publicado: (2024)
por: Liu, Jing, et al.
Publicado: (2024)
Evaluating the Effectiveness of Video Anomaly Detection in the Wild: Online Learning and Inference for Real-world Deployment
por: Yao, Shanle, et al.
Publicado: (2024)
por: Yao, Shanle, et al.
Publicado: (2024)
DA-Flow: Dual Attention Normalizing Flow for Skeleton-based Video Anomaly Detection
por: Wu, Ruituo, et al.
Publicado: (2024)
por: Wu, Ruituo, et al.
Publicado: (2024)
Deep Learning for Video Anomaly Detection: A Review
por: Wu, Peng, et al.
Publicado: (2024)
por: Wu, Peng, et al.
Publicado: (2024)
AG-VAS: Anchor-Guided Zero-Shot Visual Anomaly Segmentation with Large Multimodal Models
por: Qu, Zhen, et al.
Publicado: (2026)
por: Qu, Zhen, et al.
Publicado: (2026)
AnyAnomaly: Zero-Shot Customizable Video Anomaly Detection with LVLM
por: Ahn, Sunghyun, et al.
Publicado: (2025)
por: Ahn, Sunghyun, et al.
Publicado: (2025)
Weakly Supervised Video Anomaly Detection and Localization with Spatio-Temporal Prompts
por: Wu, Peng, et al.
Publicado: (2024)
por: Wu, Peng, et al.
Publicado: (2024)
MoECLIP: Patch-Specialized Experts for Zero-shot Anomaly Detection
por: Park, Jun Yeong, et al.
Publicado: (2026)
por: Park, Jun Yeong, et al.
Publicado: (2026)
ALARM: Automated MLLM-Based Anomaly Detection in Complex-EnviRonment Monitoring with Uncertainty Quantification
por: Zhang, Congjing, et al.
Publicado: (2025)
por: Zhang, Congjing, et al.
Publicado: (2025)
SMART: Shot-Aware Multimodal Video Moment Retrieval with Audio-Enhanced MLLM
por: Yu, An, et al.
Publicado: (2025)
por: Yu, An, et al.
Publicado: (2025)
GV-VAD : Exploring Video Generation for Weakly-Supervised Video Anomaly Detection
por: Cai, Suhang, et al.
Publicado: (2025)
por: Cai, Suhang, et al.
Publicado: (2025)
Progressive Boundary Guided Anomaly Synthesis for Industrial Anomaly Detection
por: Chen, Qiyu, et al.
Publicado: (2024)
por: Chen, Qiyu, et al.
Publicado: (2024)
Video Anomaly Detection with Structured Keywords
por: Foltz, Thomas
Publicado: (2025)
por: Foltz, Thomas
Publicado: (2025)
AnomalyClaw: A Universal Visual Anomaly Detection Agent via Tool-Grounded Refutation
por: Jiang, Xi, et al.
Publicado: (2026)
por: Jiang, Xi, et al.
Publicado: (2026)
Texture-AD: An Anomaly Detection Dataset and Benchmark for Real Algorithm Development
por: Lei, Tianwu, et al.
Publicado: (2024)
por: Lei, Tianwu, et al.
Publicado: (2024)
Unlocking Vision-Language Models for Video Anomaly Detection via Fine-Grained Prompting
por: Zou, Shu, et al.
Publicado: (2025)
por: Zou, Shu, et al.
Publicado: (2025)
Geometry-Aware Semantic Reasoning for Training Free Video Anomaly Detection
por: Zia, Ali, et al.
Publicado: (2026)
por: Zia, Ali, et al.
Publicado: (2026)
KKA: Improving Vision Anomaly Detection through Anomaly-related Knowledge from Large Language Models
por: Chen, Dong, et al.
Publicado: (2025)
por: Chen, Dong, et al.
Publicado: (2025)
AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection
por: Chao, Yuhao, et al.
Publicado: (2025)
por: Chao, Yuhao, et al.
Publicado: (2025)
URA-Net: Uncertainty-Integrated Anomaly Perception and Restoration Attention Network for Unsupervised Anomaly Detection
por: Luo, Wei, et al.
Publicado: (2026)
por: Luo, Wei, et al.
Publicado: (2026)
Is Hyperbolic Space All You Need for Medical Anomaly Detection?
por: Gonzalez-Jimenez, Alvaro, et al.
Publicado: (2025)
por: Gonzalez-Jimenez, Alvaro, et al.
Publicado: (2025)
MeLIAD: Interpretable Few-Shot Anomaly Detection with Metric Learning and Entropy-based Scoring
por: Cholopoulou, Eirini, et al.
Publicado: (2024)
por: Cholopoulou, Eirini, et al.
Publicado: (2024)
Fence Theorem: Towards Dual-Objective Semantic-Structure Isolation in Preprocessing Phase for 3D Anomaly Detection
por: Liang, Hanzhe, et al.
Publicado: (2025)
por: Liang, Hanzhe, et al.
Publicado: (2025)
Ejemplares similares
-
ACD-CLIP: Decoupling Representation and Dynamic Fusion for Zero-Shot Anomaly Detection
por: Ma, Ke, et al.
Publicado: (2025) -
Anomaly-Aware Vision-Language Adapters for Zero-Shot Anomaly Detection
por: Aqeel, Muhammad, et al.
Publicado: (2026) -
SSVP: Synergistic Semantic-Visual Prompting for Industrial Zero-Shot Anomaly Detection
por: Fu, Chenhao, et al.
Publicado: (2026) -
ViP$^2$-CLIP: Visual-Perception Prompting with Unified Alignment for Zero-Shot Anomaly Detection
por: Yang, Ziteng, et al.
Publicado: (2025) -
Rethinking Metrics and Benchmarks of Video Anomaly Detection
por: Liu, Zihao, et al.
Publicado: (2025)