Deep learning approaches to anomaly detection (AD) have recently improved the state of
the art in detection performance on complex data sets, such as large collections of images or …

Detecting poorly textured objects and estimating their 3D pose reliably is still a very
challenging problem. We introduce a simple but powerful approach to computing descriptors …

Classical approaches for one-class problems such as one-class SVM and isolation forest
require careful feature engineering when applied to structured domains like images. State-of …

Integrating computer vision and natural language processing is a novel interdisciplinary field
that has received a lot of attention recently. In this survey, we provide a comprehensive …

Anomaly synthesis strategies can effectively enhance unsupervised anomaly detection.
However, existing strategies have limitations in the coverage and controllability of anomaly …

Mathematical optimization plays a fundamental role in solving many problems in computer
vision (eg, camera calibration, image alignment, structure from motion). It is generally …

Abstract Machine learning techniques have been widely used to detect morphological
abnormalities from structural brain magnetic resonance imaging data and to support the …

Building information models (BIMs) have proven to be data-rich, object-oriented, intelligent,
and parametric digital representations of buildings to support diverse activities throughout …

Opponent modeling is the ability to use prior knowledge and observations in order to predict
the behavior of an opponent. This survey presents a comprehensive overview of existing …

Infrared thermography for quality assessment of polymer composites has gained increasing
attention with the development of various thermographic data analysis methods. However …