Evolution and Cutting-Edge Developments in Face Forgery Technology Based on Generative Models

PixelBoost 8 – Pixel Quality with 8X Highlights Boosting Enhancement

This work proposes a new GAN-based face hallucination method primarily based on the Enhanced Super-Resolution Generative Adversarial Network (ESRGAN), and presents a personalised adaptation of ESRGAN that employs the VGG16 architecture with a compact pre-trained version.

Evolution, Comparison, and Trend Prospects of Text Generated Images Based on Deep Learning

Text generated image is a hot research field of cross modal in-depth learning, which can effectively replace the traditional manual drawing and be applied in games, advertising and other industries. The existing mainstream technologies are divided into Generative Adversarial Network (GAN), transformer and diffusion mod...

Deepguardnet: A Resnet-Based Hybrid Framework for Intelligent Deepfake Image and Video Authentication

The evolution of sophisticated generative artificial intelligence has led to the rapid development of very realistic manipulated images and videos, posing substantial risks for digital trust, cyber security, and multimedia authenticity. Advanced Deepfake generation technologies result in the creation of believable forg...

Deepfake Generation and Detection in the Era of Digital Media

A YOLO enhanced deep learning model for efficient and scalable deepfake detection for real-time facial forgery recognition in digital media

Deep fake technology has significantly advanced the creation of synthetic images and videos, sparking widespread concerns about its potential misuse in spreading misinformation, violating privacy, and enabling identity theft. As these manipulations be-come increasingly sophisticated, the development of reliable detecti...

Comparative Analysis of Image Generation Based on GAN, VAE, and Diffusion Models

: The core task of image generation models is to generate visual content that meets specific requirements based on given inputs. The wide application of artificial intelligence has accelerated the development of generative technologies, and image generation has had a significant impact across various fields in real-wor...