📄 Abstract We investigate the trade-off between visual fidelity and computational efficiency. Our experiments demonstrate that the Depthwise Separable GAN reduces the model parameter count by 93.7% ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results