Background Modeling for Video Sequences by Stacked Denoising Autoencoders. - Jorge García-González 001; Juan Miguel Ortiz-de-Lazcano-Lobato; Rafael M. Luque-Baena; Miguel A. Molina-Cabello; Ezequiel López-Rubio (CAEPIA, 2018)

Background Modeling by Shifted Tilings of Stacked Denoising Autoencoders. - Jorge García-González 001; Juan Miguel Ortiz-de-Lazcano-Lobato; Rafael M. Luque-Baena; Ezequiel López-Rubio (IWINAC (2), 2019)

Foreground detection by probabilistic modeling of the features discovered by stacked denoising autoencoders in noisy video sequences. - Jorge García-González 001; Juan Miguel Ortiz-de-Lazcano-Lobato; Rafael M. Luque-Baena; Miguel A. Molina-Cabello; Ezequiel López-Rubio (Pattern Recognit. Lett., 2019)

Foreground Detection by Probabilistic Mixture Models Using Semantic Information from Deep Networks. - Jorge García-González 001; Juan Miguel Ortiz-de-Lazcano-Lobato; Rafael M. Luque-Baena; Ezequiel López-Rubio (ECAI, 2020)

Deep Autoencoder Architectures For Foreground Object Detection In Video Sequences Based On Probabilistic Mixture Models. - Jorge García-González 001; Miguel A. Molina-Cabello; Rafael M. Luque-Baena; Juan Miguel Ortiz-de-Lazcano-Lobato; Ezequiel López-Rubio (ICIP, 2020)

Adaptive estimation of optimal color transformations for deep convolutional network based homography estimation. - Miguel A. Molina-Cabello; Jorge García-González 001; Rafael Marcos Luque Baena; Karl Thurnhofer-Hemsi; Ezequiel López-Rubio (ICPR, 2020)

The effect of downsampling-upsampling strategy on foreground detection algorithms. - Miguel A. Molina-Cabello; Jorge García-González 001; Rafael M. Luque-Baena; Ezequiel López-Rubio (Artif. Intell. Rev., 2020)

Background subtraction by probabilistic modeling of patch features learned by deep autoencoders. - Jorge García-González 001; Juan Miguel Ortiz-de-Lazcano-Lobato; Rafael M. Luque-Baena; Ezequiel López-Rubio (Integr. Comput. Aided Eng., 2020)

Foreground Segmentation Improvement by Image Denoising Preprocessing Applied to Noisy Video Sequences. - Jorge García-González 001; Juan Miguel Ortiz-de-Lazcano-Lobato; Rafael Marcos Luque Baena; Ezequiel López-Rubio (SOCO, 2021)

Road pollution estimation from vehicle tracking in surveillance videos by deep convolutional neural networks. - Jorge García-González 001; Miguel A. Molina-Cabello; Rafael M. Luque-Baena; Juan Miguel Ortiz-de-Lazcano-Lobato; Ezequiel López-Rubio (Appl. Soft Comput., 2021)

Bayesian and Neural Inference on LSTM-Based Object Recognition From Tactile and Kinesthetic Information. - Francisco Pastor; Jorge García-González 001; Juan M. Gandarias; Daniel Medina; Pau Closas; Alfonso J. García-Cerezo; Jesús M. Gómez de Gabriel (IEEE Robotics Autom. Lett., 2021)

Moving Object Detection in Noisy Video Sequences Using Deep Convolutional Disentangled Representations. - Jorge García-González 001; Rafael M. Luque-Baena; Juan Miguel Ortiz-de-Lazcano-Lobato; Ezequiel López-Rubio (ICIP, 2022)

Enhanced Image Segmentation by a Novel Test Time Augmentation and Super-Resolution. - Iván García Aguilar; Jorge García-González 001; Rafael Marcos Luque Baena; Ezequiel López-Rubio; Enrique Domínguez-Merino (IWINAC (1), 2022)

Anomalous Trajectory Detection for Automated Traffic Video Surveillance. - Jose D. Fernández 001; Jorge García-González 001; Rafaela Benítez-Rochel; Miguel A. Molina-Cabello; Ezequiel López-Rubio (IWINAC (1), 2022)

Encoding Generative Adversarial Networks for Defense Against Image Classification Attacks. - José M. Pérez-Bravo; José A. Rodríguez-Rodríguez; Jorge García-González 001; Miguel A. Molina-Cabello; Karl Thurnhofer-Hemsi; Ezequiel López-Rubio (IWINAC (1), 2022)

Vehicle Overtaking Hazard Detection over Onboard Cameras Using Deep Convolutional Networks. - Jorge García-González 001; Iván García Aguilar; Daniel Medina; Rafael Marcos Luque Baena; Ezequiel López-Rubio; Enrique Domínguez (SOCO, 2022)

Optimized instance segmentation by super-resolution and maximal clique generation. - Iván García Aguilar; Jorge García-González 001; Rafael M. Luque-Baena; Ezequiel López-Rubio; Enrique Domínguez (Integr. Comput. Aided Eng., 2023)

Automated detection of vehicles with anomalous trajectories in traffic surveillance videos. - Jose David Fernández Rodriguez; Jorge García-González 001; Rafaela Benítez-Rochel; Miguel A. Molina-Cabello; Gonzalo Ramos-Jiménez; Ezequiel López-Rubio (Integr. Comput. Aided Eng., 2023)

Automated labeling of training data for improved object detection in traffic videos by fine-tuned deep convolutional neural networks. - Iván García Aguilar; Jorge García-González 001; Rafael Marcos Luque Baena; Ezequiel López-Rubio (Pattern Recognit. Lett., 2023)

Object detection in traffic videos: an optimized approach using super-resolution and maximal clique algorithm. - Iván García Aguilar; Jorge García-González 001; Rafael Marcos Luque Baena; Ezequiel López-Rubio (Neural Comput. Appl., 2023)

Novel Positional Encoding Methods for Neural Rendering. - Daniel Molina-Pinel; Jorge García-González 001; Enrique Domínguez; Ezequiel López-Rubio (SOCO (2), 2024)

DyNeRFactor: Temporally consistent intrinsic scene decomposition for dynamic NeRFs. - Mario Alfonso-Arsuaga; Jorge García-González 001; Andrea Castiella-Aguirrezabala; Miguel Andrés Alonso; Elena Garces 001 (Comput. Graph., 2024)

Detection of dangerously approaching vehicles over onboard cameras by speed estimation from apparent size. - Iván García Aguilar; Jorge García-González 001; Daniel Medina; Rafael Marcos Luque Baena; Enrique Domínguez; Ezequiel López-Rubio (Neurocomputing, 2024)

Neuralux: Improving the decomposition of single-illumination multiview outdoor scenes. - Mario Alfonso-Arsuaga; Andrea Castiella-Aguirrezabala; Jorge García-González 001; Jesús Bonilla; Jorge López-Moreno (Comput. Graph., 2025)

PHYSPLAT: A Framework for Photorealistic Hybrid Simulation of Real and Synthetic Elements using 3D Gaussian Splatting. - Mario Alfonso-Arsuaga; Henar Dominguez-Elvira; Jorge Casas-Guerrero; Andrea Castiella-Aguirrezabala; Lorenzo Costabile-Dominguez; Jorge García-González 001; Maria Naranjo-Almeida; Marc Comino-Trinidad; Jorge Lopez-Moreno (WACV, 2026)

Estimating the Speed of Nearby Vehicles with a Single Onboard Camera by Smooth Kernel Regression. - Mónica López-Pola; Iván García Aguilar; Jorge García-González 001; Ezequiel López-Rubio (Int. J. Neural Syst., 2026)