Photorealistic Image Synthesis with GANs
Photorealistic image synthesis involves generating images that are indistinguishable from real photographs. This requires high-resolution outputs, precise texture generation, and accurate lighting effects. Advanced GAN architectures like StyleGAN2 and BigGAN have pushed the boundaries of photorealism, achieving remarkable results in face generation, landscape creation, and product design. Techniques such as progressive training, perceptual loss functions, and adaptive instance normalization contribute to the enhanced realism and detail in AI-generated visuals.