Image de couverture de livre

Leveraging Multimodal LLM Descriptions of Activity for Explainable Semi-Supervised Video Anomaly Detection

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Mumcu, Furkan, Jones, Michael J., Cherian, Anoop, Yilmaz, Yasin
Format:	Preprint
Publié:	2025
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

Is Video Anomaly Detection Misframed? Evidence from LLM-Based and Multi-Scene Models
par: Mumcu, Furkan, et autres
Publié: (2026)

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)

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

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

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

Injecting Explainability and Lightweight Design into Weakly Supervised Video Anomaly Detection Systems
par: Jiang, Wen-Dong, et autres
Publié: (2024)

Instance-Aligned Captions for Explainable Video Anomaly Detection
par: Song, Inpyo, et autres
Publié: (2026)

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

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

Temporal Divide-and-Conquer Anomaly Actions Localization in Semi-Supervised Videos with Hierarchical Transformer
par: Osman, Nada, et autres
Publié: (2024)

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

Weakly Supervised Video Anomaly Detection with Anomaly-Connected Components and Intention Reasoning
par: Wang, Yu, et autres
Publié: (2026)

Enhancing Weakly Supervised Multimodal Video Anomaly Detection through Text Guidance
par: Sun, Shengyang, et autres
Publié: (2026)

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

LATERN: Test-Time Context-Aware Explainable Video Anomaly Detection
par: Piehl, Mitchell, et autres
Publié: (2026)

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

Learning Event Completeness for Weakly Supervised Video Anomaly Detection
par: Wang, Yu, et autres
Publié: (2025)

Distilling Aggregated Knowledge for Weakly-Supervised Video Anomaly Detection
par: Dalvi, Jash, et autres
Publié: (2024)

Cross-Domain Learning for Video Anomaly Detection with Limited Supervision
par: Jain, Yashika, et autres
Publié: (2024)

Cross Pseudo Labeling For Weakly Supervised Video Anomaly Detection
par: Lee, Dayeon, et autres
Publié: (2026)

DRL-Guided Neural Batch Sampling for Semi-Supervised Pixel-Level Anomaly Detection
par: Noghredeh, Amirhossein Khadivi, et autres
Publié: (2025)

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

Text Prompt with Normality Guidance for Weakly Supervised Video Anomaly Detection
par: Yang, Zhiwei, et autres
Publié: (2024)

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

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

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

Language-guided Open-world Video Anomaly Detection under Weak Supervision
par: Liu, Zihao, et autres
Publié: (2025)

Cross-Modal Fusion and Attention Mechanism for Weakly Supervised Video Anomaly Detection
par: Ghadiya, Ayush, et autres
Publié: (2024)

Learning Prompt-Enhanced Context Features for Weakly-Supervised Video Anomaly Detection
par: Pu, Yujiang, et autres
Publié: (2023)

GlanceVAD: Exploring Glance Supervision for Label-efficient Video Anomaly Detection
par: Zhang, Huaxin, et autres
Publié: (2024)

Uncertainty-Weighted Image-Event Multimodal Fusion for Video Anomaly Detection
par: Jeong, Sungheon, et autres
Publié: (2025)

VADTree: Explainable Training-Free Video Anomaly Detection via Hierarchical Granularity-Aware Tree
par: Li, Wenlong, et autres
Publié: (2025)

Multimodal Attention-Enhanced Feature Fusion-based Weekly Supervised Anomaly Violence Detection
par: Kaneko, Yuta, et autres
Publié: (2024)

Semi-Supervised Learning for Deep Causal Generative Models
par: Ibrahim, Yasin, et autres
Publié: (2024)

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

RefineVAD: Semantic-Guided Feature Recalibration for Weakly Supervised Video Anomaly Detection
par: Lee, Junhee, et autres
Publié: (2025)