activity
20182022
collaborators

6 papers

cs.LG2022

Slack Norm Support Vector Data Description

Shervin R. Arashloo

The support vector data description (SVDD) approach serves as a de facto standard for one-class classification where the learning task entails inferring the smallest hyper-sphere t…

cs.CV2019

Unseen Face Presentation Attack Detection Using Class-Specific Sparse One-Class Multiple Kernel Fusion Regression

Shervin Rahimzadeh Arashloo

The paper addresses face presentation attack detection in the challenging conditions of an unseen attack scenario where the system is exposed to novel presentation attacks that wer…

cs.LG2019

Multi-Task Kernel Null-Space for One-Class Classification

Shervin Rahimzadeh Arashloo, Josef Kittler

The one-class kernel spectral regression (OC-KSR), the regression-based formulation of the kernel null-space approach has been found to be an effective Fisher criterion-based metho…

cs.LG2019

Robust One-Class Kernel Spectral Regression

Shervin Rahimzadeh Arashloo, Josef Kittler

The kernel null-space technique and its regression-based formulation (called one-class kernel spectral regression, a.k.a. OC-KSR) is known to be an effective and computationally at…

cs.CV2018

Client-Specific Anomaly Detection for Face Presentation Attack Detection

Shervin Rahimzadeh Arashloo, Josef Kittler

The one-class anomaly detection approach has previously been found to be effective in face presentation attack detection, especially in an \textit{unseen} attack scenario, where th…

cs.LG2018

One-Class Kernel Spectral Regression

Shervin Rahimzadeh Arashloo, Josef Kittler

The paper introduces a new efficient nonlinear one-class classifier formulated as the Rayleigh quotient criterion optimisation. The method, operating in a reproducing kernel Hilber…