In this work, we introduce and discuss Quaternion Generative Adversarial Networks, a variant of generative adversarial networks that uses quaternion-valued inputs, weights and intermediate network representation
Security Insights Additional navigation options main 1Branch0Tags Code README MIT license Official PyTorch repository for: Eleonora Grassucci, Edoardo Cicero,Danilo Comminiello, "Quaternion Generative Adversarial Networks",Generative Adversarial Learning: Architectures and Applications, editors: Dr Roozbeh Raza...
Evaluating GANs (Generative Adversarial Networks) is difficult – unlike classification problems there is no final accuracy to compare against, for instance. For my OpenAI Spring Scholars project, I focused on different ways to understand & to evaluate image synthesis GANs, using the approach of Dist...
Evaluating GANs (Generative Adversarial Networks) is difficult – unlike classification problems there is no final accuracy to compare against, for instance. For my OpenAI Spring Scholars project, I focused on different ways to understand & to evaluate image synthesis GANs, using the approach of Dist...
Jaiswal, A., AbdAlmageed, W., Wu, Y., Natarajan, P.: CapsuleGAN: generative adversarial capsule network. In: Leal-Taixé, L., Roth, S. (eds.) ECCV 2018. LNCS, vol. 11131, pp. 526–535. Springer, Cham (2019).https://doi.org/10.1007/978-3-030-11015-4_38 ...
Yu C. Attention based data hiding with generative adversarial networks. Proc AAAI Conf Artif Intell, 2020; 34(01): 1120-8. https://doi.org/10.1609/aaai.v34i01.5463. Google Scholar [58] Zhang H, Wang H, Cao Y, Shen C, Li Y, Robust data hiding using inverse gradient attention, 2020...
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Quaternionized versions of standard (real-valued) neural network layers have shown to lead to networks that are sparse and as effective as their real-valued counterparts. In this work, we explore their usefulness in the context of the Keyword Spotting ta
To address these issues related to complexity and information loss, we propose a family of quaternion-valued generative adversarial networks (QGANs). QGANs exploit the properties of quaternion algebra, e.g., the Hamilton product, that allows to process channels as a single entity and capture ...
Quaternion generative adversarial networks. In Generative Adversarial Learning: Architectures and Applications; Springer: Berlin/Heidelberg, Germany, 2022; pp. 57–86. [Google Scholar] Figure 1. Representation of the color pixel as a quaternion number. The yellow button is a pixel in the image. ...