Diffusion models represent a promising avenue for image generation, having demonstrated
competitive performance in pose-guided person image generation. However, existing …

Fashion knowledge encourages people to properly dress and faces not only physiological
necessity of users, but also the requirement of social practices and activities. It usually …

Appearance and pose-guided human generation is a burgeoning field that has captured
significant attention. This subject's primary objective is to transfer pose information from a …

The mechanism of existing style transfer algorithms is by minimizing a hybrid loss function to
push the generated image toward high similarities in both content and style. However, this …

The current 3D human pose estimators face challenges in adapting to new datasets due to
the scarcity of 2D-3D pose pairs in target domain training sets. We present the Multi …

Human pose estimation is a challenging task due to its structured data sequence nature.
Existing methods primarily focus on pair-wise interaction of body joints, which is insufficient …

Abstract Generative Neural Radiance Field (GNeRF) models, which extract implicit 3D
representations from 2D images, have recently been shown to produce realistic images …

Traditional guided image translation methods, based on encoder–decoder or U-Net
structures, often struggle with complex or contrasting images. To address this, we introduce …

The study of ancient writings has great value for archaeology and philology. Essential forms
of material are photographic characters, but manual photographic character recognition is …

The fashion industry is on the verge of an unprecedented change. The implementation of
machine learning, computer vision, and artificial intelligence (AI) in fashion applications is …