| Empirical generalization study: Unsupervised domain adaptation vs. domain generalization methods for semantic segmentation in the wild FJ Piva, D De Geus, G Dubbelman Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 23 | 2023 |
| Exploiting image translations via ensemble self-supervised learning for unsupervised domain adaptation FJ Piva, G Dubbelman Computer Vision and Image Understanding 234, 103745, 2023 | 15 | 2023 |
| Learning to predict collision risk from simulated video data TJ Schoonbeek, FJ Piva, HR Abdolhay, G Dubbelman 2022 IEEE Intelligent Vehicles Symposium (IV), 943-951, 2022 | 10 | 2022 |
| Exploring the benefits of vision foundation models for unsupervised domain adaptation BB Englert, FJ Piva, T Kerssies, D De Geus, G Dubbelman Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 3 | 2024 |
| Una Estrategia de Acoplamiento Conservativa y Monótona para Mallas No Coincidentes en Problemas Multifísica Particionados PS Vera, FJ Piva, GR Rodríguez, L Garelli, MA Storti Mecánica Computacional 35 (26), 1541-1559, 2017 | | 2017 |
| Supplementary Material–Empirical Generalization Study: Unsupervised Domain Adaptation vs. Domain Generalization Methods for Semantic Segmentation in the Wild FJ Piva, D de Geus, G Dubbelman | | |
