DROCC: Deep Robust One-Class Classification

28 February 2020

Moksh Jain

Papers citing "DROCC: Deep Robust One-Class Classification"

45 / 95 papers shown

Title
Red PANDA: Disambiguating Anomaly Detection by Removing Nuisance Factors Niv Cohen Jonathan Kahana Yedid Hoshen 16 3 0 07 Jul 2022
Augment to Detect Anomalies with Continuous Labelling Vahid Reza Khazaie A. Wong Y. Mohsenzadeh 25 1 0 03 Jul 2022
R2-AD2: Detecting Anomalies by Analysing the Raw Gradient Jan-Philipp Schulze Philip Sperl Ana Ruaductoiu Carla Sagebiel Konstantin Böttinger 11 2 0 21 Jun 2022
Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution Xueying Ding Lingxiao Zhao L. Akoglu OODD 30 22 0 15 Jun 2022
Perturbation Learning Based Anomaly Detection Jinyu Cai Jicong Fan AAML 21 26 0 06 Jun 2022
Machine Learning for Microcontroller-Class Hardware: A Review Swapnil Sayan Saha S. Sandha Mani B. Srivastava 24 118 0 29 May 2022
Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images Philipp Liznerski Lukas Ruff Robert A. Vandermeulen Billy Joe Franks Klaus-Robert Muller Marius Kloft UQCV 45 44 0 23 May 2022
TracInAD: Measuring Influence for Anomaly Detection Hugo Thimonier Fabrice Popineau Arpad Rimmel Bich-Liên Doan Fabrice Daniel TDI 11 6 0 03 May 2022
Feature anomaly detection system (FADS) for intelligent manufacturing Anthony P. Garland Kevin M. Potter Matt Smith 12 2 0 21 Apr 2022
A Revealing Large-Scale Evaluation of Unsupervised Anomaly Detection Algorithms Maxime Alvarez Jean-Charles Verdier D'Jeff K. Nkashama Marc Frappier Pierre Martin Tardif F. Kabanza 26 17 0 21 Apr 2022
Semi-supervised anomaly detection algorithm based on KL divergence (SAD-KL) C. Lee Kibae Lee 36 4 0 28 Mar 2022
No Shifted Augmentations (NSA): compact distributions for robust self-supervised Anomaly Detection Mohamed Yousef Marcel R. Ackermann Unmesh Kurup Tom E. Bishop OODD OOD 37 3 0 19 Mar 2022
Improving State-of-the-Art in One-Class Classification by Leveraging Unlabeled Data F. Bagirov Dmitry Ivanov A. Shpilman 20 0 0 14 Mar 2022
Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series Enyan Dai Jie Chen BDL AI4TS 8 70 0 16 Feb 2022
Time Series Anomaly Detection by Cumulative Radon Features Yedid Hoshen AI4TS 11 2 0 08 Feb 2022
Data Invariants to Understand Unsupervised Out-of-Distribution Detection Lars Doorenbos Raphael Sznitman Pablo Márquez-Neila OODD 27 6 0 26 Nov 2021
Efficient Anomaly Detection Using Self-Supervised Multi-Cue Tasks Loic Jezequel Ngoc-Son Vu Jean Beaudet A. Histace 29 19 0 24 Nov 2021
OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the Boundary Nikolaos Dionelis Mehrdad Yaghoobi Sotirios A. Tsaftaris OODD 20 6 0 28 Oct 2021
Multi-Class Anomaly Detection Suresh Singh Minwei Luo Yu Li 19 1 0 28 Oct 2021
A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges Mohammadreza Salehi Hossein Mirzaei Dan Hendrycks Yixuan Li M. Rohban Mohammad Sabokrou OOD 38 191 0 26 Oct 2021
A Survey on Proactive Customer Care: Enabling Science and Steps to Realize it Viswanath Ganapathy Sauptik Dhar Olimpiya Saha Pelin Kurt Garberson Javad Heydari Mohak Shah 13 1 0 11 Oct 2021
Probabilistic Robust Autoencoders for Outlier Detection Ofir Lindenbaum Yariv Aizenbud Y. Kluger 14 5 0 01 Oct 2021
Enhancing Unsupervised Anomaly Detection with Score-Guided Network Zongyuan Huang Baohua Zhang Guoqiang Hu Longyuan Li Yanyan Xu Yaohui Jin 29 16 0 10 Sep 2021
Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set Framework Ammar Mansoor Kamoona A. Gostar A. Bab-Hadiashar R. Hoseinnezhad 17 16 0 27 Aug 2021
Discriminative-Generative Representation Learning for One-Class Anomaly Detection X. Xia Xizhou Pan Xing He Jingfei Zhang Ning Ding Lin Ma 24 4 0 27 Jul 2021
Anomaly Detection: How to Artificially Increase your F1-Score with a Biased Evaluation Protocol Damien Fourure Muhammad Usama Javaid N. Posocco Simon Tihon 25 36 0 30 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 21 31 0 09 Jun 2021
Shifting Transformation Learning for Out-of-Distribution Detection Sina Mohseni Arash Vahdat J. Yadawa OODD 10 7 0 07 Jun 2021
Do We Really Need to Learn Representations from In-domain Data for Outlier Detection? Zhisheng Xiao Qing Yan Y. Amit OOD UQCV 17 18 0 19 May 2021
DOC3-Deep One Class Classification using Contradictions Sauptik Dhar Bernardo Gonzalez Torres 22 3 0 17 May 2021
Understanding the Effect of Bias in Deep Anomaly Detection Ziyu Ye Yuxin Chen Haitao Zheng 9 18 0 16 May 2021
A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection Shelly Sheynin Sagie Benaim Lior Wolf 12 79 0 29 Apr 2021
Multi-view Deep One-class Classification: A Systematic Exploration Siqi Wang Jiyuan Liu Guang Yu Xinwang Liu Sihang Zhou En Zhu Yuexiang Yang Jianping Yin 16 1 0 27 Apr 2021
Unsupervised Learning of Multi-level Structures for Anomaly Detection Songmin Dai Jide Li Lu Wang Congcong Zhu Yifan Wu Xiaoqiang Li 15 0 0 25 Apr 2021
Fine-grained Anomaly Detection via Multi-task Self-Supervision Loic Jezequel Ngoc-Son Vu Jean Beaudet A. Histace 28 6 0 20 Apr 2021
Neural Transformation Learning for Deep Anomaly Detection Beyond Images Chen Qiu Timo Pfrommer Marius Kloft Stephan Mandt Maja R. Rudolph ViT AI4TS 6 121 0 30 Mar 2021
SSD: A Unified Framework for Self-Supervised Outlier Detection Vikash Sehwag M. Chiang Prateek Mittal OODD 31 330 0 22 Mar 2021
Self-Taught Semi-Supervised Anomaly Detection on Upper Limb X-rays A. Spahr Behzad Bozorgtabar Jean-Philippe Thiran 19 16 0 19 Feb 2021
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training Lue Tao Lei Feng Jinfeng Yi Sheng-Jun Huang Songcan Chen AAML 26 71 0 09 Feb 2021
Multiresolution Knowledge Distillation for Anomaly Detection Mohammadreza Salehi Niousha Sadjadi Soroosh Baselizadeh M. Rohban Hamid R. Rabiee 15 430 0 22 Nov 2020
An Experimental Study of Semantic Continuity for Deep Learning Models Shangxi Wu Dongyuan Lu Xian Zhao Lizhang Chen Jitao Sang 28 2 0 19 Nov 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 29 48 0 19 Oct 2020
A Unifying Review of Deep and Shallow Anomaly Detection Lukas Ruff Jacob R. Kauffmann Robert A. Vandermeulen G. Montavon Wojciech Samek Marius Kloft Thomas G. Dietterich Klaus-Robert Muller UQCV 20 779 0 24 Sep 2020
Explainable Deep One-Class Classification Philipp Liznerski Lukas Ruff Robert A. Vandermeulen Billy Joe Franks Marius Kloft Klaus-Robert Muller 15 198 0 03 Jul 2020
Deep Weakly-supervised Anomaly Detection Guansong Pang Chunhua Shen Huidong Jin Anton van den Hengel 25 90 0 30 Oct 2019