Marzouk, AhmedAhmedMarzoukBarros, PabloPabloBarrosEppe, ManfredManfredEppeWermter, StefanStefanWermter2022-04-252022-04-252019-07International Joint Conference on Neural Networks (IJCNN 2019)http://hdl.handle.net/11420/12358We propose an extension of the Boundary Equilibrium GAN (BEGAN) neural network, named Conditional BEGAN (CBEGAN), as a general generative and transformational approach for data processing. As a novelty, the system is able of both data generation and transformation under conditional input. We evaluate our approach for conditional image generation and editing using five controllable attributes for images of faces from the CelebA dataset: age, smiling, cheekbones, eyeglasses and gender. We perform a set of objective quantitative experiments to evaluate the model's performance and a qualitative user study to evaluate how humans assess the generated and edited images. Both evaluations yield coinciding results which show that the generated facial attributes are recognizable in more than 80% of all new testing samples.enConditional GANimage generationimage translationConference Paper10.1109/IJCNN.2019.8852164Conference Paper