Poster "anomaly detection" Papers
52 papers found • Page 1 of 2
Conference
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.
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.
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.
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
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.
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.
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.
Stealthy Yet Effective: Distribution-Preserving Backdoor Attacks on Graph Classification
Xiaobao Wang, Ruoxiao Sun, Yujun Zhang 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.
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.
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.
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.
GeneralAD: Anomaly Detection Across Domains by Attending to Distorted Features
Luc Sträter, Mohammadreza Salehi, Efstratios Gavves et al.
Learning Anomalies with Normality Prior for Unsupervised Video Anomaly Detection
Haoyue Shi, Le Wang, Sanping Zhou et al.
Learning to Detect Multi-class Anomalies with Just One Normal Image Prompt
Bin-Bin Gao
Learning Unified Reference Representation for Unsupervised Multi-class Anomaly Detection
Liren He, Zhengkai Jiang, Jinlong Peng et al.
MF-CLR: Multi-Frequency Contrastive Learning Representation for Time Series
Jufang Duan, Wei Zheng, Yangzhou Du et al.
MoEAD: A Parameter-efficient Model for Multi-class Anomaly Detection
Shiyuan Meng, Wenchao Meng, Qihang Zhou et al.
ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models
Dongha Kim, Jaesung Hwang, Jongjin Lee et al.
Online Adaptive Anomaly Thresholding with Confidence Sequences
Sophia Sun, Abishek Sankararaman, Balakrishnan Narayanaswamy
Online Isolation Forest
Filippo Leveni, Guilherme Weigert Cassales, Bernhard Pfahringer et al.
PixOOD: Pixel-Level Out-of-Distribution Detection
Tomas Vojir, Jan Sochman, Jiri Matas
Real Appearance Modeling for More General Deepfake Detection
Jiahe Tian, Yu Cai, Xi Wang et al.
RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection
Ximiao Zhang, Min Xu, Xiuzhuang Zhou
Single-Model Attribution of Generative Models Through Final-Layer Inversion
Mike Laszkiewicz, Jonas Ricker, Johannes Lederer et al.
Sobolev Space Regularised Pre Density Models
Mark Kozdoba, Binyamin Perets, Shie Mannor
Timer: Generative Pre-trained Transformers Are Large Time Series Models
Yong Liu, Haoran Zhang, Chenyu Li et al.
TransFusion -- A Transparency-Based Diffusion Model for Anomaly Detection
Matic Fučka, Vitjan Zavrtanik, Danijel Skocaj