Exam NCA-GENM Topic 1 Question 306 Discussion

Actual exam question for NVIDIA's NCA-GENM exam
Question #: 306
Topic #: 1

You're training a conditional GAN (cGAN) to generate images of handwritten digits conditioned on the digit label. You notice that the generated images are blurry and lack fine details, even after extensive training. Which of the following techniques could you implement to improve the sharpness and realism of the generated images?

A. Increase the dimensionality of the latent space. B. Use spectral normalization on both the generator and discriminator. C. Add batch normalization layers to the generator and discriminator. D. Implement a perceptual loss function in addition to the adversarial loss. E. Increase the learning rate of the generator.

Suggested Answer: D Vote an answer

Perceptual loss functions, which compare high-level features extracted by a pre-trained network, encourage the generator to create images that are more perceptually realistic and detailed. Spectral normalization helps stabilize training and can prevent the discriminator from overpowering the generator, but it doesn't directly address the lack of detail. Increasing latent space dimensionality and adding batch normalization are general techniques that might help, but perceptual loss is more targeted for improving image quality. Increasing the learning rate might destabilize training.

by Channing at Nov 09, 2025, 08:51 PM

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