Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images

23 May 2022

Papers citing "Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images"

8 / 8 papers shown

Title
A graph neural network-based model with Out-of-Distribution Robustness for enhancing Antiretroviral Therapy Outcome Prediction for HIV-1 Giulia Di Teodoro F. Siciliano V. Guarrasi A. Vandamme Valeria Ghisetti Anders Sönnerborg Maurizio Zazzi Fabrizio Silvestri L. Palagi 61 8 0 24 Feb 2025
Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey Ruiyao Xu Kaize Ding 50 5 0 17 Feb 2025
Enhancing Anomaly Detection Generalization through Knowledge Exposure: The Dual Effects of Augmentation Mohammad Akhavan Anvari Rojina Kashefi Vahid Reza Khazaie Mohammad Khalooei Mohammad Sabokrou 25 0 0 15 Jun 2024
Continual Unsupervised Out-of-Distribution Detection Lars Doorenbos Raphael Sznitman Pablo Márquez-Neila OODD 29 0 0 04 Jun 2024
FiLo: Zero-Shot Anomaly Detection by Fine-Grained Description and High-Quality Localization Zhaopeng Gu Bingke Zhu Guibo Zhu Yingying Chen Hao Li Ming Tang Jinqiao Wang 24 15 0 21 Apr 2024
Set Learning for Accurate and Calibrated Models Lukas Muttenthaler Robert A. Vandermeulen Qiuyi Zhang Thomas Unterthiner Klaus-Robert Muller 15 2 0 05 Jul 2023
Improving neural network representations using human similarity judgments Lukas Muttenthaler Lorenz Linhardt Jonas Dippel Robert A. Vandermeulen Katherine L. Hermann Andrew Kyle Lampinen Simon Kornblith 27 29 0 07 Jun 2023
Open-Set Recognition: a Good Closed-Set Classifier is All You Need? S. Vaze Kai Han Andrea Vedaldi Andrew Zisserman BDL 158 401 0 12 Oct 2021