9 citations · 13 across the 7 of their papers we have counts for
6 papers · 1 filter
GenLCA: 3D Diffusion for Full-Body Avatars from In-the-Wild Videos
Yiqian Wu, Rawal Khirodkar, Egor Zakharov +6
We present GenLCA, a diffusion-based generative model for generating and editing photorealistic full-body avatars from text and image inputs. The generated avatars are faithful to…
Text-based Animatable 3D Avatars with Morphable Model Alignment
Yiqian Wu, Malte Prinzler, Xiaogang Jin +1
The generation of high-quality, animatable 3D head avatars from text has enormous potential in content creation applications such as games, movies, and embodied virtual assistants.…
Mask Factory: Towards High-quality Synthetic Data Generation for Dichotomous Image Segmentation
Haotian Qian, YD Chen, Shengtao Lou +3
Dichotomous Image Segmentation (DIS) tasks require highly precise annotations, and traditional dataset creation methods are labor intensive, costly, and require extensive domain ex…
StyleTex: Style Image-Guided Texture Generation for 3D Models
Zhiyu Xie, Yuqing Zhang, Xiangjun Tang +4
Style-guided texture generation aims to generate a texture that is harmonious with both the style of the reference image and the geometry of the input mesh, given a reference style…
Portrait3D: Text-Guided High-Quality 3D Portrait Generation Using Pyramid Representation and GANs Prior
Yiqian Wu, Hao Xu, Xiangjun Tang +5
Existing neural rendering-based text-to-3D-portrait generation methods typically make use of human geometry prior and diffusion models to obtain guidance. However, relying solely o…
Enhancing the Authenticity of Rendered Portraits with Identity-Consistent Transfer Learning
Luyuan Wang, Yiqian Wu, Yongliang Yang +2
Despite rapid advances in computer graphics, creating high-quality photo-realistic virtual portraits is prohibitively expensive. Furthermore, the well-know ''uncanny valley'' effec…