An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile Robots

The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection

(2021) Paul Bergmann et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

A Unifying Review of Deep and Shallow Anomaly Detection

(2021) Lukas Ruff et al.   PROCEEDINGS OF THE IEEE

The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation

(2021) Hermann Blum et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field

(2016) Peter Christiansen et al.   SENSORS

High-Resolution SAR Image Classification via Deep Convolutional Autoencoders

(2015) Jie Geng et al.   IEEE Geoscience and Remote Sensing Letters

Online data-driven anomaly detection in autonomous robots

(2014) Eliahu Khalastchi et al.   KNOWLEDGE AND INFORMATION SYSTEMS

Anomaly detection

(2009) Varun Chandola et al.   ACM COMPUTING SURVEYS

80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition

(2008) A. Torralba et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE