Category: NeurIPS

  • Ensembles of Generative Adversarial Networks

    Yaxing Wang, Lichao Zhang, Joost van de Weijer Read Full Paper → Ensembles are a popular way to improve results of discriminative CNNs. The combination of several networks trained starting from different initializations improves results significantly. In this paper we investigate the usage of ensembles of GANs. The specific nature of GANs opens up several new ways […]

  • Invertible Conditional GANs for image editing

    Guim Perarnau, Joost van de Weijer, Bogdan Raducanu, Jose M. Álvarez Read Full Paper → Generative Adversarial Networks (GANs) have recently demonstrated to successfully approximate complex data distributions. A relevant extension of this model is conditional GANs (cGANs), where the introduction of external information allows to determine specific representations of the generated images. In this work, we evaluate […]