Generative adversarial networks (GANs), a novel framework for training generative models
in an adversarial setup, have attracted significant attention in recent years. The two …

To minimize the effects of age variation in face recognition, previous work either extracts
identity-related discriminative features by minimizing the correlation between identity-and …

Abstract 3D face reconstruction is the most captivating topic in biometrics with the advent of
deep learning and readily available graphical processing units. This paper explores the …

With the rapid development of face forgery techniques, the existing frame-based deepfake
video detection methods have fell into a dilemma that frame-based methods may fail when …

We present SinDiffusion, leveraging denoising diffusion models to capture internal
distribution of patches from a single natural image. SinDiffusion significantly improves the …

With the development of deep learning technology, the facial manipulation system has
become powerful and easy to use. Such systems can modify the attributes of the given facial …

Forecasting the road surface crack images with given present crack images is an important
task to assist the road survivors in planning for their next lay down of road with the required …

Abstract Machine learning (ML) applications in medical artificial intelligence (AI) systems
have shifted from traditional and statistical methods to increasing application of deep …

Recent works for face editing usually manipulate the latent space of StyleGAN via the linear
semantic directions. However, they usually suffer from the entanglement of facial attributes …

Face Age Progression (FAP) refers to synthesizing face images while simulating ageing
effects, thus enabling predicting the future appearance of an individual. The generation of …