"anomaly detection" Papers
74 papers found • Page 2 of 2
Conference
GeneralAD: Anomaly Detection Across Domains by Attending to Distorted Features
Luc Sträter, Mohammadreza Salehi, Efstratios Gavves et al.
GOODAT: Towards Test-Time Graph Out-of-Distribution Detection
Luzhi Wang, Di Jin, He Zhang 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
Root Cause Analysis in Microservice Using Neural Granger Causal Discovery
Cheng-Ming Lin, Ching Chang, Wei-Yao Wang et al.
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
Soft Contrastive Learning for Time Series
Seunghan Lee, Taeyoung Park, Kibok Lee
Timer: Generative Pre-trained Transformers Are Large Time Series Models
Yong Liu, Haoran Zhang, Chenyu Li et al.
TimesURL: Self-Supervised Contrastive Learning for Universal Time Series Representation Learning
jiexi Liu, Songcan Chen
TransFusion -- A Transparency-Based Diffusion Model for Anomaly Detection
Matic Fučka, Vitjan Zavrtanik, Danijel Skocaj
TSLANet: Rethinking Transformers for Time Series Representation Learning
Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen et al.
UP2ME: Univariate Pre-training to Multivariate Fine-tuning as a General-purpose Framework for Multivariate Time Series Analysis
Yunhao Zhang, Liu Minghao, Shengyang Zhou et al.
VCP-CLIP: A visual context prompting model for zero-shot anomaly segmentation
Zhen Qu, Xian Tao, Mukesh Prasad et al.
When and How Does In-Distribution Label Help Out-of-Distribution Detection?
Xuefeng Du, Yiyou Sun, Sharon Li