• Comprehensive Review: This survey provides a thorough analysis of deepfake technology, focusing on both generation and detection.
• Technological Advances: Discusses cutting-edge techniques including Variational Autoencoders, Generative Adversarial Networks, and Diffusion Models.
• Task Definitions: Offers a unified approach to defining tasks associated with deepfake technology.
• Related Sub-Fields: Examines developments in face swapping, face reenactment, talking face generation, and facial attribute editing, along with forgery detection.

The development of deepfake technology has significant implications for privacy, digital media, and security. This comprehensive survey aims to benchmark performance across various platforms, offering insights into the current state and future direction of deepfake technology.