2024 Poster "anomaly detection" Papers
16 papers found
Beyond Individual Input for Deep Anomaly Detection on Tabular Data
Hugo Thimonier, Fabrice Popineau, Arpad Rimmel et al.
ICML 2024poster
Contamination-Resilient Anomaly Detection via Adversarial Learning on Partially-Observed Normal and Anomalous Data
Wenxi Lv, Qinliang Su, Hai Wan et al.
ICML 2024poster
Continuous Memory Representation for Anomaly Detection
Joo Chan Lee, Taejune Kim, Eunbyung Park et al.
ECCV 2024posterarXiv:2402.18293
19
citations
FedREDefense: Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error
Yueqi Xie, Minghong Fang, Neil Gong
ICML 2024poster
GeneralAD: Anomaly Detection Across Domains by Attending to Distorted Features
Luc Sträter, Mohammadreza Salehi, Efstratios Gavves et al.
ECCV 2024posterarXiv:2407.12427
27
citations
Learning Anomalies with Normality Prior for Unsupervised Video Anomaly Detection
Haoyue Shi, Le Wang, Sanping Zhou et al.
ECCV 2024poster
1
citations
MF-CLR: Multi-Frequency Contrastive Learning Representation for Time Series
Jufang Duan, Wei Zheng, Yangzhou Du et al.
ICML 2024poster
ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models
Dongha Kim, Jaesung Hwang, Jongjin Lee et al.
ICML 2024poster
Online Adaptive Anomaly Thresholding with Confidence Sequences
Sophia Sun, Abishek Sankararaman, Balakrishnan Narayanaswamy
ICML 2024poster
Online Isolation Forest
Filippo Leveni, Guilherme Weigert Cassales, Bernhard Pfahringer et al.
ICML 2024poster
Real Appearance Modeling for More General Deepfake Detection
Jiahe Tian, Yu Cai, Xi Wang et al.
ECCV 2024poster
12
citations
Single-Model Attribution of Generative Models Through Final-Layer Inversion
Mike Laszkiewicz, Jonas Ricker, Johannes Lederer et al.
ICML 2024poster
Sobolev Space Regularised Pre Density Models
Mark Kozdoba, Binyamin Perets, Shie Mannor
ICML 2024poster
Timer: Generative Pre-trained Transformers Are Large Time Series Models
Yong Liu, Haoran Zhang, Chenyu Li et al.
ICML 2024poster
VCP-CLIP: A visual context prompting model for zero-shot anomaly segmentation
Zhen Qu, Xian Tao, Mukesh Prasad et al.
ECCV 2024posterarXiv:2407.12276
55
citations
When and How Does In-Distribution Label Help Out-of-Distribution Detection?
Xuefeng Du, Yiyou Sun, Sharon Li
ICML 2024poster