4 citations · 4 across the 3 of their papers we have counts for
5 papers
SeeABLE: Soft Discrepancies and Bounded Contrastive Learning for Exposing Deepfakes
Nicolas Larue, Ngoc-Son Vu, Vitomir Struc +2
Modern deepfake detectors have achieved encouraging results, when training and test images are drawn from the same data collection. However, when these detectors are applied to ima…
Anomaly Detection via Multi-Scale Contrasted Memory
Loic Jezequel, Ngoc-Son Vu, Jean Beaudet +1
Deep anomaly detection (AD) aims to provide robust and efficient classifiers for one-class and unbalanced settings. However current AD models still struggle on edge-case normal sam…
Efficient Anomaly Detection Using Self-Supervised Multi-Cue Tasks
Loic Jezequel, Ngoc-Son Vu, Jean Beaudet +1
Anomaly detection is important in many real-life applications. Recently, self-supervised learning has greatly helped deep anomaly detection by recognizing several geometric transfo…
Fine-grained Anomaly Detection via Multi-task Self-Supervision
Loic Jezequel, Ngoc-Son Vu, Jean Beaudet +1
Detecting anomalies using deep learning has become a major challenge over the last years, and is becoming increasingly promising in several fields. The introduction of self-supervi…
Improving Texture Categorization with Biologically Inspired Filtering
Ngoc-Son Vu, Thanh Phuong Nguyen, Christophe Garcia
Within the domain of texture classification, a lot of effort has been spent on local descriptors, leading to many powerful algorithms. However, preprocessing techniques have receiv…