"anomaly detection" Papers
74 papers found • Page 1 of 2
Conference
3D-RAD: A Comprehensive 3D Radiology Med-VQA Dataset with Multi-Temporal Analysis and Diverse Diagnostic Tasks
Xiaotang Gai, Jiaxiang Liu, Yichen Li et al.
ADPretrain: Advancing Industrial Anomaly Detection via Anomaly Representation Pretraining
Xincheng Yao, Yan Luo, Zefeng Qian et al.
Adversarially Robust Anomaly Detection through Spurious Negative Pair Mitigation
Hossein Mirzaei Sadeghlou, Mojtaba Nafez, Jafar Habibi et al.
An Evidence-Based Post-Hoc Adjustment Framework for Anomaly Detection Under Data Contamination
Sukanya Patra, Souhaib Ben Taieb
Anomaly Detection by an Ensemble of Random Pairs of Hyperspheres
Walid Durani, Collin Leiber, Khalid Durani et al.
AutoSciDACT: Automated Scientific Discovery through Contrastive Embedding and Hypothesis Testing
Sam Bright-Thonney, Christina Reissel, Gaia Grosso et al.
BlockScan: Detecting Anomalies in Blockchain Transactions
Jiahao Yu, Xian Wu, Hao Liu et al.
CATCH: Channel-Aware Multivariate Time Series Anomaly Detection via Frequency Patching
Xingjian Wu, Xiangfei Qiu, Zhengyu Li et al.
CausalRivers - Scaling up benchmarking of causal discovery for real-world time-series
Gideon Stein, Maha Shadaydeh, Jan Blunk et al.
Channel Matters: Estimating Channel Influence for Multivariate Time Series
Muyao Wang, Zeke Xie, Bo Chen et al.
DFM: Differentiable Feature Matching for Anomaly Detection
Wu Sheng, Yimi Wang, Xudong Liu et al.
DiffGAD: A Diffusion-based Unsupervised Graph Anomaly Detector
Jinghan Li, Yuan Gao, Jinda Lu et al.
Effective and Efficient Representation Learning for Flight Trajectories
Shuo Liu, Wenbin Li, Di Yao et al.
Exploring Intrinsic Normal Prototypes within a Single Image for Universal Anomaly Detection
Wei Luo, Yunkang Cao, Haiming Yao et al.
Fairness-aware Anomaly Detection via Fair Projection
Feng Xiao, Xiaoying Tang, Jicong Fan
Filter or Compensate: Towards Invariant Representation from Distribution Shift for Anomaly Detection
Zining Chen, Xingshuang Luo, Weiqiu Wang et al.
Kaputt: A Large-Scale Dataset for Visual Defect Detection
Sebastian Höfer, Dorian Henning, Artemij Amiranashvili et al.
Language-Assisted Feature Transformation for Anomaly Detection
EungGu Yun, Heonjin Ha, Yeongwoo Nam et al.
MANTA: A Large-Scale Multi-View and Visual-Text Anomaly Detection Dataset for Tiny Objects
Lei Fan, Dongdong Fan, Zhiguang Hu et al.
MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning
Ylli Sadikaj, Hongkuan Zhou, Lavdim Halilaj et al.
Multivariate Time Series Anomaly Detection with Idempotent Reconstruction
Xin Sun, Heng Zhou, Chao Li
NoBOOM: Chemical Process Datasets for Industrial Anomaly Detection
Dennis Wagner, Fabian Hartung, Justus Arweiler et al.
Normal and Abnormal Pathology Knowledge-Augmented Vision-Language Model for Anomaly Detection in Pathology Images
Jinsol Song, Jiamu Wang, Anh Nguyen et al.
NOVA: A Benchmark for Rare Anomaly Localization and Clinical Reasoning in Brain MRI
Cosmin Bercea, Jun Li, Philipp Raffler et al.
Odd-One-Out: Anomaly Detection by Comparing with Neighbors
Ankan Kumar Bhunia, Changjian Li, Hakan Bilen
One-for-More: Continual Diffusion Model for Anomaly Detection
Xiaofan Li, Xin Tan, Zhuo Chen et al.
PatchGuard: Adversarially Robust Anomaly Detection and Localization through Vision Transformers and Pseudo Anomalies
Mojtaba Nafez, Amirhossein Koochakian, Arad Maleki et al.
PhysDiff: A Physically-Guided Diffusion Model for Multivariate Time Series Anomaly Detection
Long Li, Wanghu Chen, Wencheng Zhang et al.
Quantifying Statistical Significance of Deep Nearest Neighbor Anomaly Detection via Selective Inference
Mizuki Niihori, Shuichi Nishino, Teruyuki Katsuoka et al.
Revisiting Graph Contrastive Learning on Anomaly Detection: A Structural Imbalance Perspective
Yiming Xu, Zhen Peng, Bin Shi et al.
Salvaging the Overlooked: Leveraging Class-Aware Contrastive Learning for Multi-Class Anomaly Detection
Lei Fan, Junjie Huang, Donglin Di et al.
Scalable, Explainable and Provably Robust Anomaly Detection with One-Step Flow Matching
Zhong Li, Qi Huang, Yuxuan Zhu et al.
Selective Learning for Deep Time Series Forecasting
Yisong Fu, Zezhi Shao, Chengqing Yu et al.
Self-Perturbed Anomaly-Aware Graph Dynamics for Multivariate Time-Series Anomaly Detection
Jinyu Cai, Yuan Xie, Glynnis Lim et al.
Stealthy Yet Effective: Distribution-Preserving Backdoor Attacks on Graph Classification
Xiaobao Wang, Ruoxiao Sun, Yujun Zhang et al.
Structured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection
Dongchan Cho, Jiho Han, Keumyeong Kang et al.
Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models
Hoang Khoi Nguyen Do, Truc Nguyen, Malik Hassanaly et al.
The Temporal Graph of Bitcoin Transactions
Vahid Jalili
TimeInf: Time Series Data Contribution via Influence Functions
Yizi Zhang, Jingyan Shen, Xiaoxue Xiong et al.
TimeMixer++: A General Time Series Pattern Machine for Universal Predictive Analysis
Shiyu Wang, Jiawei LI, Xiaoming Shi et al.
Toward Long-Tailed Online Anomaly Detection through Class-Agnostic Concepts
Chiao-An Yang, Kuan-Chuan Peng, Raymond A. Yeh
Unifying Reconstruction and Density Estimation via Invertible Contraction Mapping in One-Class Classification
Xiaolei Wang, Tianhong Dai, Huihui Bai et al.
A Comprehensive Augmentation Framework for Anomaly Detection
Lin Jiang, Yaping Yan
A Diffusion-Based Framework for Multi-Class Anomaly Detection
Haoyang He, Jiangning Zhang, Hongxu Chen et al.
Beyond Individual Input for Deep Anomaly Detection on Tabular Data
Hugo Thimonier, Fabrice Popineau, Arpad Rimmel et al.
Contamination-Resilient Anomaly Detection via Adversarial Learning on Partially-Observed Normal and Anomalous Data
Wenxi Lv, Qinliang Su, Hai Wan et al.
Continuous Memory Representation for Anomaly Detection
Joo Chan Lee, Taejune Kim, Eunbyung Park et al.
Explain Temporal Black-Box Models via Functional Decomposition
Linxiao Yang, Yunze Tong, Xinyue Gu et al.
FedREDefense: Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error
Yueqi Xie, Minghong Fang, Neil Gong
Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation
Guan Gui, Bin-Bin Gao, Jun Liu et al.