Image de couverture de livre

Is Video Anomaly Detection Misframed? Evidence from LLM-Based and Multi-Scene Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Mumcu, Furkan, Jones, Michael J., Cherian, Anoop, Yilmaz, Yasin
Format:	Preprint
Publié:	2026
Sujets:	Computer Vision and Pattern Recognition
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Leveraging Multimodal LLM Descriptions of Activity for Explainable Semi-Supervised Video Anomaly Detection
par: Mumcu, Furkan, et autres
Publié: (2025)

ComplexVAD: Detecting Interaction Anomalies in Video
par: Mumcu, Furkan, et autres
Publié: (2025)

LLM-Guided Agentic Object Detection for Open-World Understanding
par: Mumcu, Furkan, et autres
Publié: (2025)

Multimodal Attack Detection for Action Recognition Models
par: Mumcu, Furkan, et autres
Publié: (2024)

Universal and Efficient Detection of Adversarial Data through Nonuniform Impact on Network Layers
par: Mumcu, Furkan, et autres
Publié: (2025)

QVAD: A Question-Centric Agentic Framework for Efficient and Training-Free Video Anomaly Detection
par: Bekit, Lokman, et autres
Publié: (2026)

Socially-Weighted Alignment: A Game-Theoretic Framework for Multi-Agent LLM Systems
par: Mumcu, Furkan, et autres
Publié: (2026)

MMHOI: Modeling Complex 3D Multi-Human Multi-Object Interactions
par: Kogashi, Kaen, et autres
Publié: (2025)

COPRA: Conditional Parameter Adaptation with Reinforcement Learning for Video Anomaly Detection
par: Jacob, Darryl Cherian, et autres
Publié: (2026)

Agentic AI-Empowered Dynamic Survey Framework
par: Mumcu, Furkan, et autres
Publié: (2026)

Aligning Step-by-Step Instructional Diagrams to Video Demonstrations
par: Zhang, Jiahao, et autres
Publié: (2023)

Temporally Grounding Instructional Diagrams in Unconstrained Videos
par: Zhang, Jiahao, et autres
Publié: (2024)

Improving Open-World Object Localization by Discovering Background
par: Singh, Ashish, et autres
Publié: (2025)

A Hierarchical Benchmark of Foundation Models for Dermatology
par: Yuceyalcin, Furkan, et autres
Publié: (2026)

Manual-PA: Learning 3D Part Assembly from Instruction Diagrams
par: Zhang, Jiahao, et autres
Publié: (2024)

Detecting Adversarial Examples
par: Mumcu, Furkan, et autres
Publié: (2024)

Detecting Adversarial Data via Provable Adversarial Noise Amplification
par: Mumcu, Furkan, et autres
Publié: (2026)

Holmes-VAD: Towards Unbiased and Explainable Video Anomaly Detection via Multi-modal LLM
par: Zhang, Huaxin, et autres
Publié: (2024)

TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models
par: Ni, Haomiao, et autres
Publié: (2024)

Unveiling Context-Related Anomalies: Knowledge Graph Empowered Decoupling of Scene and Action for Human-Related Video Anomaly Detection
par: Chen, Chenglizhao, et autres
Publié: (2024)

Exploring the Magnitude-Shape Plot Framework for Anomaly Detection in Crowded Video Scenes
par: Wang, Zuzheng, et autres
Publié: (2024)

HyCoVAD: A Hybrid SSL-LLM Model for Complex Video Anomaly Detection
par: Hemmatyar, Mohammad Mahdi, et autres
Publié: (2025)

Simplifying Traffic Anomaly Detection with Video Foundation Models
par: Orlova, Svetlana, et autres
Publié: (2025)

Learn Suspected Anomalies from Event Prompts for Video Anomaly Detection
par: Tao, Chenchen, et autres
Publié: (2024)

LLMPhy: Parameter-Identifiable Physical Reasoning Combining Large Language Models and Physics Engines
par: Cherian, Anoop, et autres
Publié: (2024)

Frequency-Guided Diffusion Model with Perturbation Training for Skeleton-Based Video Anomaly Detection
par: Tan, Xiaofeng, et autres
Publié: (2024)

THYME: Temporal Hierarchical-Cyclic Interactivity Modeling for Video Scene Graphs in Aerial Footage
par: Nguyen, Trong-Thuan, et autres
Publié: (2025)

Towards Video Anomaly Retrieval from Video Anomaly Detection: New Benchmarks and Model
par: Wu, Peng, et autres
Publié: (2023)

HyperGLM: HyperGraph for Video Scene Graph Generation and Anticipation
par: Nguyen, Trong-Thuan, et autres
Publié: (2024)

Open-Vocabulary Video Anomaly Detection
par: Wu, Peng, et autres
Publié: (2023)

Vision-Language Models Assisted Unsupervised Video Anomaly Detection
par: Jiang, Yalong, et autres
Publié: (2024)

Video Anomaly Detection and Explanation via Large Language Models
par: Lv, Hui, et autres
Publié: (2024)

Dual Conditioned Motion Diffusion for Pose-Based Video Anomaly Detection
par: Wang, Hongsong, et autres
Publié: (2024)

SpinBench: Perspective and Rotation as a Lens on Spatial Reasoning in VLMs
par: Zhang, Yuyou, et autres
Publié: (2025)

Pseudo Anomalies Are All You Need: Diffusion-Based Generation for Weakly-Supervised Video Anomaly Detection
par: Hashimoto, Satoshi, et autres
Publié: (2025)

IPFormer-VideoLLM: Enhancing Multi-modal Video Understanding for Multi-shot Scenes
par: Liang, Yujia, et autres
Publié: (2025)

Enhance Multi-Scale Spatial-Temporal Coherence for Configurable Video Anomaly Detection
par: Cheng, Kai, et autres
Publié: (2023)

AnyAnomaly: Zero-Shot Customizable Video Anomaly Detection with LVLM
par: Ahn, Sunghyun, et autres
Publié: (2025)

VADMamba: Exploring State Space Models for Fast Video Anomaly Detection
par: Lyu, Jiahao, et autres
Publié: (2025)

Harnessing Large Language Models for Training-free Video Anomaly Detection
par: Zanella, Luca, et autres
Publié: (2024)