Cover Image

CADIC: Continual Anomaly Detection Based on Incremental Coreset

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Gen, Deng, Zhipeng, Man, Junfeng
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Noise-Tolerant Coreset-Based Class Incremental Continual Learning
by: Mucllari, Edison, et al.
Published: (2025)

Memory Efficient Continual Learning for Edge-Based Visual Anomaly Detection
by: Barusco, Manuel, et al.
Published: (2025)

Enhancing Multimodal In-Context Learning for Image Classification through Coreset Optimization
by: Chen, Huiyi, et al.
Published: (2025)

Towards Continual Visual Anomaly Detection in the Medical Domain
by: Barusco, Manuel, et al.
Published: (2025)

Diffusion-Augmented Coreset Expansion for Scalable Dataset Distillation
by: Abbasi, Ali, et al.
Published: (2024)

Are Anomaly Scores Telling the Whole Story? A Benchmark for Multilevel Anomaly Detection
by: Cao, Tri, et al.
Published: (2024)

Continual Visual Anomaly Detection on the Edge: Benchmark and Efficient Solutions
by: Barusco, Manuel, et al.
Published: (2026)

ELFS: Label-Free Coreset Selection with Proxy Training Dynamics
by: Zheng, Haizhong, et al.
Published: (2024)

Transformer-Based Framework for Motion Capture Denoising and Anomaly Detection in Medical Rehabilitation
by: Cai, Yeming, et al.
Published: (2025)

Geometry-Aware Uncertainty Coresets for Robust Visual In-Context Learning in Histopathology
by: Erick, Franciskus Xaverius, et al.
Published: (2026)

I Detect What I Don't Know: Incremental Anomaly Learning with Stochastic Weight Averaging-Gaussian for Oracle-Free Medical Imaging
by: Yadav, Nand Kumar, et al.
Published: (2025)

Compensating Visual Insufficiency with Stratified Language Guidance for Long-Tail Class Incremental Learning
by: Wang, Xi, et al.
Published: (2026)

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

MALT: Multi-scale Action Learning Transformer for Online Action Detection
by: Yang, Zhipeng, et al.
Published: (2024)

Detecting Contextual Anomalies by Discovering Consistent Spatial Regions
by: Yang, Zhengye, et al.
Published: (2025)

AnomalyClaw: A Universal Visual Anomaly Detection Agent via Tool-Grounded Refutation
by: Jiang, Xi, et al.
Published: (2026)

Rethinking Metrics and Benchmarks of Video Anomaly Detection
by: Liu, Zihao, et al.
Published: (2025)

AdapTS: Lightweight Teacher-Student Approach for Multi-Class and Continual Visual Anomaly Detection
by: Barusco, Manuel, et al.
Published: (2026)

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

CEAT: Continual Expansion and Absorption Transformer for Non-Exemplar Class-Incremental Learning
by: Gao, Xinyuan, et al.
Published: (2024)

Efficient and Robust Quantization-aware Training via Adaptive Coreset Selection
by: Huang, Xijie, et al.
Published: (2023)

Dynamic Object Queries for Transformer-based Incremental Object Detection
by: Zhang, Jichuan, et al.
Published: (2024)

Dynamic Distinction Learning: Adaptive Pseudo Anomalies for Video Anomaly Detection
by: Lappas, Demetris, et al.
Published: (2024)

Weakly-Supervised Spatiotemporal Anomaly Detection
by: Gianchandani, Urvi, et al.
Published: (2026)

MMAD: A Comprehensive Benchmark for Multimodal Large Language Models in Industrial Anomaly Detection
by: Jiang, Xi, et al.
Published: (2024)

AA-CLIP: Enhancing Zero-shot Anomaly Detection via Anomaly-Aware CLIP
by: Ma, Wenxin, et al.
Published: (2025)

Towards Video Anomaly Retrieval from Video Anomaly Detection: New Benchmarks and Model
by: Wu, Peng, et al.
Published: (2023)

AnomalySD: Few-Shot Multi-Class Anomaly Detection with Stable Diffusion Model
by: Yan, Zhenyu, et al.
Published: (2024)

Versatile Incremental Learning: Towards Class and Domain-Agnostic Incremental Learning
by: Park, Min-Yeong, et al.
Published: (2024)

Weakly Supervised Video Anomaly Detection and Localization with Spatio-Temporal Prompts
by: Wu, Peng, et al.
Published: (2024)

SALAD -- Semantics-Aware Logical Anomaly Detection
by: Fučka, Matic, et al.
Published: (2025)

Normal-Abnormal Guided Generalist Anomaly Detection
by: Wang, Yuexin, et al.
Published: (2025)

Anomaly Detection by Effectively Leveraging Synthetic Images
by: Kang, Sungho, et al.
Published: (2025)

A Comprehensive Augmentation Framework for Anomaly Detection
by: Lin, Jiang, et al.
Published: (2023)

Interactive Explainable Anomaly Detection for Industrial Settings
by: Gramelt, Daniel, et al.
Published: (2024)

Unsupervised Anomaly Detection in Brain MRI via Disentangled Anatomy Learning
by: Yang, Tao, et al.
Published: (2025)

URA-Net: Uncertainty-Integrated Anomaly Perception and Restoration Attention Network for Unsupervised Anomaly Detection
by: Luo, Wei, et al.
Published: (2026)

DualTeacher: Bridging Coexistence of Unlabelled Classes for Semi-supervised Incremental Object Detection
by: Yuan, Ziqi, et al.
Published: (2023)

Beyond Prompt Degradation: Prototype-guided Dual-pool Prompting for Incremental Object Detection
by: Zhang, Yaoteng, et al.
Published: (2026)

AIFIND: Artifact-Aware Interpreting Fine-Grained Alignment for Incremental Face Forgery Detection
by: Wang, Hao, et al.
Published: (2026)