Stationary foreground detection for video-surveillance based on foreground and motion history images. - Diego Ortego; Juan C. SanMiguel (AVSS, 2013)

Multi-feature stationary foreground detection for crowded video-surveillance. - Diego Ortego; Juan C. SanMiguel (ICIP, 2014)

Long-Term Stationary Object Detection Based on Spatio-Temporal Change Detection. - Diego Ortego; Juan C. SanMiguel; José M. Martínez 001 (IEEE Signal Process. Lett., 2015)

Rejection based multipath reconstruction for background estimation in SBMnet 2016 dataset. - Diego Ortego; Juan C. SanMiguel; José M. Martínez 001 (ICPR, 2016)

Rejection based multipath reconstruction for background estimation in video sequences with stationary objects. - Diego Ortego; Juan C. SanMiguel; José M. Martínez 001 (Comput. Vis. Image Underst., 2016)

Stand-alone quality estimation of background subtraction algorithms. - Diego Ortego; Juan C. SanMiguel; José M. Martínez 001 (Comput. Vis. Image Underst., 2017)

VisDrone-VDT2018: The Vision Meets Drone Video Detection and Tracking Challenge Results. - Pengfei Zhu 001; Longyin Wen; Dawei Du; Xiao Bian; Haibin Ling; Qinghua Hu; Haotian Wu 006; Qinqin Nie; Hao Cheng 010; Chenfeng Liu; Xiaoyu Liu 005; Wenya Ma; et al. (ECCV Workshops (5), 2018)

Abandoned Object Detection in Video-Surveillance: Survey and Comparison. - Elena Luna; Juan Carlos San Miguel; Diego Ortego; José M. Martínez 001 (Sensors, 2018)

On guiding video object segmentation. - Diego Ortego; Kevin McGuinness; Juan C. SanMiguel; Eric Arazo; José M. Martínez 001; Noel E. O'Connor (CBMI, 2019)

Unsupervised Label Noise Modeling and Loss Correction. - Eric Arazo; Diego Ortego; Paul Albert; Noel E. O'Connor; Kevin McGuinness (ICML, 2019)

Hierarchical Improvement of Foreground Segmentation Masks in Background Subtraction. - Diego Ortego; Juan C. SanMiguel; José M. Martínez 001 (IEEE Trans. Circuits Syst. Video Technol., 2019)

Towards Robust Learning with Different Label Noise Distributions. - Diego Ortego; Eric Arazo; Paul Albert; Noel E. O'Connor; Kevin McGuinness (ICPR, 2020)

Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning. - Eric Arazo; Diego Ortego; Paul Albert; Noel E. O'Connor; Kevin McGuinness (IJCNN, 2020)

Domain Randomization for Object Counting. - Enric Moreu; Kevin McGuinness; Diego Ortego; Noel E. O'Connor (AICS, 2021)

How Important is Importance Sampling for Deep Budgeted Training? - Eric Arazo; Diego Ortego; Paul Albert; Noel E. O'Connor; Kevin McGuinness (BMVC, 2021)

Multi-Objective Interpolation Training for Robustness To Label Noise. - Diego Ortego; Eric Arazo; Paul Albert; Noel E. O'Connor; Kevin McGuinness (CVPR, 2021)

Unsupervised Contrastive Learning of Sound Event Representations. - Eduardo Fonseca; Diego Ortego; Kevin McGuinness; Noel E. O'Connor; Xavier Serra (ICASSP, 2021)

ReLaB: Reliable Label Bootstrapping for Semi-Supervised Learning. - Paul Albert; Diego Ortego; Eric Arazo; Noel E. O'Connor; Kevin McGuinness (IJCNN, 2021)

Addressing out-of-distribution label noise in webly-labelled data. - Paul Albert; Diego Ortego; Eric Arazo; Noel E. O'Connor; Kevin McGuinness (WACV, 2022)

Block-SCL: Blocking Matters for Supervised Contrastive Learning in Product Matching. - Mario Almagro; David Jiménez; Diego Ortego; Emilio J. Almazán; Eva Martínez (CoRR, 2022)

LEA: Improving Sentence Similarity Robustness to Typos Using Lexical Attention Bias. - Mario Almagro; Emilio J. Almazán; Diego Ortego; David Jiménez (KDD, 2023)

Prototypical Extreme Multi-label Classification with a Dynamic Margin Loss. - Kunal Dahiya; Diego Ortego; David Jiménez (CoRR, 2024)

Prototypical Extreme Multi-label Classification with a Dynamic Margin Loss. - Kunal Dahiya; Diego Ortego; David Jimenez-Cabello (NAACL (Long Papers), 2025)