Defocus Effect

The defocus effect, or control over depth of field in images, is a key area of research aiming to improve image quality and realism, particularly in computational photography and virtual/augmented reality. Current research focuses on developing novel algorithms and architectures, such as neural radiance fields (NeRFs) and generative adversarial networks (GANs), to synthesize and manipulate defocus effects from multiple camera inputs or single images, often leveraging techniques like aperture rendering and ray tracing. These advancements enable more realistic image rendering and creative post-capture editing capabilities, impacting fields ranging from smartphone photography to 3D scene modeling.