7 citations · 7 across the 6 of their papers we have counts for
6 papers
High-Fidelity 3D Facial Avatar Synthesis with Controllable Fine-Grained Expressions
Yikang He, Jichao Zhang, Wei Wang +2
Facial expression editing methods can be mainly categorized into two types based on their architectures: 2D-based and 3D-based methods. The former lacks 3D face modeling capabiliti…
Stable-Hair v2: Real-World Hair Transfer via Multiple-View Diffusion Model
Kuiyuan Sun, Yuxuan Zhang, Jichao Zhang +4
While diffusion-based methods have shown impressive capabilities in capturing diverse and complex hairstyles, their ability to generate consistent and high-quality multi-view outpu…
Multi-focal Conditioned Latent Diffusion for Person Image Synthesis
Jiaqi Liu, Jichao Zhang, Paolo Rota +1
The Latent Diffusion Model (LDM) has demonstrated strong capabilities in high-resolution image generation and has been widely employed for Pose-Guided Person Image Synthesis (PGPIS…
UVMap-ID: A Controllable and Personalized UV Map Generative Model
Weijie Wang, Jichao Zhang, Chang Liu +5
Recently, diffusion models have made significant strides in synthesizing realistic 2D human images based on provided text prompts. Building upon this, researchers have extended 2D…
3D-Aware Semantic-Guided Generative Model for Human Synthesis
Jichao Zhang, Enver Sangineto, Hao Tang +4
Generative Neural Radiance Field (GNeRF) models, which extract implicit 3D representations from 2D images, have recently been shown to produce realistic images representing rigid/s…
Controllable Person Image Synthesis with Spatially-Adaptive Warped Normalization
Jichao Zhang, Aliaksandr Siarohin, Hao Tang +4
Controllable person image generation aims to produce realistic human images with desirable attributes such as a given pose, cloth textures, or hairstyles. However, the large spatia…