Cover Image

AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chao, Yuhao, Liu, Jie, Tang, Jie, Wu, Gangshan
Format:	Preprint
Published:	2025
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

No Need For Real Anomaly: MLLM Empowered Zero-Shot Video Anomaly Detection
by: Dai, Zunkai, et al.
Published: (2026)

Sketch and Refine: Towards Fast and Accurate Lane Detection
by: Chen, Chao, et al.
Published: (2024)

EMIT: Enhancing MLLMs for Industrial Anomaly Detection via Difficulty-Aware GRPO
by: Guan, Wei, et al.
Published: (2025)

Pure-Pass: Fine-Grained, Adaptive Masking for Dynamic Token-Mixing Routing in Lightweight Image Super-Resolution
by: Wu, Junyu, et al.
Published: (2025)

AFR-CLIP: Enhancing Zero-Shot Industrial Anomaly Detection with Stateless-to-Stateful Anomaly Feature Rectification
by: Yuan, Jingyi, et al.
Published: (2025)

CATANet: Efficient Content-Aware Token Aggregation for Lightweight Image Super-Resolution
by: Liu, Xin, et al.
Published: (2025)

IAD-R1: Reinforcing Consistent Reasoning in Industrial Anomaly Detection
by: Li, Yanhui, et al.
Published: (2025)

Syn-GRPO: Self-Evolving Data Synthesis for MLLM Perception Reasoning
by: Huang, Qihan, et al.
Published: (2025)

Boosting MLLM Reasoning with Text-Debiased Hint-GRPO
by: Huang, Qihan, et al.
Published: (2025)

The Evolution of Video Anomaly Detection: A Unified Framework from DNN to MLLM
by: Gao, Shibo, et al.
Published: (2025)

CXR-AD: Component X-ray Image Dataset for Industrial Anomaly Detection
by: Bai, Haoyu, et al.
Published: (2025)

Towards Efficient Pixel Labeling for Industrial Anomaly Detection and Localization
by: Li, Hanxi, et al.
Published: (2024)

IPAD: Industrial Process Anomaly Detection Dataset
by: Liu, Jinfan, et al.
Published: (2024)

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

Component-aware Unsupervised Logical Anomaly Generation for Industrial Anomaly Detection
by: Tong, Xuan, et al.
Published: (2025)

ADPretrain: Advancing Industrial Anomaly Detection via Anomaly Representation Pretraining
by: Yao, Xincheng, et al.
Published: (2025)

HeadHunt-VAD: Hunting Robust Anomaly-Sensitive Heads in MLLM for Tuning-Free Video Anomaly Detection
by: Cai, Zhaolin, et al.
Published: (2025)

Disentangled Textual Priors for Diffusion-based Image Super-Resolution
by: Jiang, Lei, et al.
Published: (2026)

Deep Industrial Image Anomaly Detection: A Survey
by: Liu, Jiaqi, et al.
Published: (2023)

On the Problem of Consistent Anomalies in Zero-Shot Industrial Anomaly Detection
by: Le-Gia, Tai, et al.
Published: (2025)

Industrial Anomaly Detection and Localization Using Weakly-Supervised Residual Transformers
by: Li, Hanxi, et al.
Published: (2023)

Vad-R1: Towards Video Anomaly Reasoning via Perception-to-Cognition Chain-of-Thought
by: Huang, Chao, et al.
Published: (2025)

A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization
by: Chen, Qiyu, et al.
Published: (2024)

Center-aware Residual Anomaly Synthesis for Multi-class Industrial Anomaly Detection
by: Chen, Qiyu, et al.
Published: (2025)

GTPT: Group-based Token Pruning Transformer for Efficient Human Pose Estimation
by: Wang, Haonan, et al.
Published: (2024)

GLAD: Generative Language-Assisted Visual Tracking for Low-Semantic Templates
by: Luo, Xingyu, et al.
Published: (2026)

MIRAGE: Model-agnostic Industrial Realistic Anomaly Generation and Evaluation for Visual Anomaly Detection
by: Hu, Jinwei, et al.
Published: (2026)

Progressive Boundary Guided Anomaly Synthesis for Industrial Anomaly Detection
by: Chen, Qiyu, et al.
Published: (2024)

Open-Vocabulary Spatio-Temporal Action Detection
by: Wu, Tao, et al.
Published: (2024)

Towards Explainable Industrial Anomaly Detection via Knowledge-Guided Latent Reasoning
by: Chen, Peng, et al.
Published: (2026)

AnomalyNCD: Towards Novel Anomaly Class Discovery in Industrial Scenarios
by: Huang, Ziming, et al.
Published: (2024)

Towards Efficient Pixel Labeling for Industrial Anomaly Detection and Localization
by: Wu, Jingqi, et al.
Published: (2025)

AnoRefiner: Anomaly-Aware Group-Wise Refinement for Zero-Shot Industrial Anomaly Detection
by: Huang, Dayou, et al.
Published: (2025)

Towards High-Resolution Industrial Image Anomaly Detection
by: Zhang, Ximiao, et al.
Published: (2025)

Text-Guided Multimodal Unified Industrial Anomaly Detection
by: Li, Zewen, et al.
Published: (2026)

Multimodal Industrial Anomaly Detection by Crossmodal Feature Mapping
by: Costanzino, Alex, et al.
Published: (2023)

Multimodal Industrial Anomaly Detection via Geometric Prior
by: Li, Min, et al.
Published: (2026)

Breaking the Bias: Recalibrating the Attention of Industrial Anomaly Detection
by: Chen, Xin, et al.
Published: (2024)

Anomaly Multi-classification in Industrial Scenarios: Transferring Few-shot Learning to a New Task
by: Liu, Jie, et al.
Published: (2024)

Real-IAD Variety: Pushing Industrial Anomaly Detection Dataset to a Modern Era
by: Zhu, Wenbing, et al.
Published: (2025)