Marcella Astrid

Arif Mahmood

IEEE Trans. Neural Networks Learn. Syst., October, 2024

Exploiting autoencoder's weakness to generate pseudo anomalies.

[BibT_eX]

[DOI]

Neural Comput. Appl., August, 2024

FakeFormer: Efficient Vulnerability-Driven Transformers for Generalisable Deepfake Detection.

[BibT_eX]

[DOI]

CoRR, 2024

Detecting Audio-Visual Deepfakes with Fine-Grained Inconsistencies.

[BibT_eX]

[DOI]

Enjie Ghorbel

CoRR, 2024

Statistics-aware Audio-visual Deepfake Detector.

[BibT_eX]

[DOI]

Enjie Ghorbel

CoRR, 2024

Constricting Normal Latent Space for Anomaly Detection with Normal-only Training Data.

[BibT_eX]

[DOI]

CoRR, 2024

LAA-Net: Localized Artifact Attention Network for High-Quality Deepfakes Detection.

[BibT_eX]

[DOI]

CoRR, 2024

Targeted Augmented Data for Audio Deepfake Detection.

[BibT_eX]

[DOI]

Enjie Ghorbel

Proceedings of the 32nd European Signal Processing Conference, 2024

LAA-Net: Localized Artifact Attention Network for Quality-Agnostic and Generalizable Deepfake Detection.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

PseudoBound: Limiting the anomaly reconstruction capability of one-class classifiers using pseudo anomalies.

[BibT_eX]

[DOI]

Neurocomputing, 2023

2022

Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2022

Limiting Reconstruction Capability of Autoencoders Using Moving Backward Pseudo Anomalies.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Ubiquitous Robots, 2022

2021

Cleaning Label Noise with Clusters for Minimally Supervised Anomaly Detection.

[BibT_eX]

[DOI]

CoRR, 2021

Domain-Robust Pedestrian-View Intersection Classification.

[BibT_eX]

[DOI]

Jae-Yeong Lee

Proceedings of the International Conference on Information and Communication Technology Convergence, 2021

An Anomaly Detection System via Moving Surveillance Robots with Human Collaboration.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Synthetic Temporal Anomaly Guided End-to-End Video Anomaly Detection.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Small Object Detection using Context and Attention.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence in Information and Communication, 2021

Deep Visual Anomaly Detection with Negative Learning.

[BibT_eX]

[DOI]

Jin Ha Lee

Proceedings of the Frontiers of Computer Vision - 27th International Workshop, 2021

Learning Not to Reconstruct Anomalies.

[BibT_eX]

[DOI]

Jae-Yeong Lee

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020

For Safer Navigation: Pedestrian-View Intersection Classification.

[BibT_eX]

[DOI]

Jin Ha Lee

Jae-Yeong Lee

Proceedings of the International Conference on Information and Communication Technology Convergence, 2020

CLAWS: Clustering Assisted Weakly Supervised Learning with Normalcy Suppression for Anomalous Event Detection.

[BibT_eX]

[DOI]

Arif Mahmood

Proceedings of the Computer Vision - ECCV 2020, 2020

Old Is Gold: Redefining the Adversarially Learned One-Class Classifier Training Paradigm.

[BibT_eX]

[DOI]

Jin-Ha Lee

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

SmoothMix: a Simple Yet Effective Data Augmentation to Train Robust Classifiers.

[BibT_eX]

[DOI]

Jin-Ha Lee

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2018

CNN based Sentence Classification with Semantic Features using Word Clustering.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Information and Communication Technology Convergence, 2018

Rank selection of CP-decomposed convolutional layers with variational Bayesian matrix factorization.

[BibT_eX]

[DOI]

Beom-Su Seo

Proceedings of the 20th International Conference on Advanced Communication Technology, 2018

2017

CP-decomposition with Tensor Power Method for Convolutional Neural Networks compression.

[BibT_eX]

[DOI]