19 citations · 51 across the 12 of their papers we have counts for
13 papers
OMGTex: One-stage Multi-style Facial Texture Reconstruction without Geometry Guidance
Zitong Xiao, Yuda Qiu, Zisheng Ye +1
We propose OMGTex, an end-to-end diffusion-based framework for reconstructing high-quality and editable facial UV textures from multi-style facial images. Existing texture reconstr…
HairOrbit: Multi-view Aware 3D Hair Modeling from Single Portraits
Leyang Jin, Yujian Zheng, Bingkui Tong +3
Reconstructing strand-level 3D hair from a single-view image is highly challenging, especially when preserving consistent and realistic attributes in unseen regions. Existing metho…
TexSpot: 3D Texture Enhancement with Spatially-uniform Point Latent Representation
Ziteng Lu, Yushuang Wu, Chongjie Ye +7
High-quality 3D texture generation remains a fundamental challenge due to the view-inconsistency inherent in current mainstream multi-view diffusion pipelines. Existing representat…
Condition Matters in Full-head 3D GANs
Heyuan Li, Huimin Zhang, Yuda Qiu +10
Conditioning is crucial for stable training of full-head 3D GANs. Without any conditioning signal, the model suffers from severe mode collapse, making it impractical to training. H…
AvatarTex: High-Fidelity Facial Texture Reconstruction from Single-Image Stylized Avatars
Yuda Qiu, Zitong Xiao, Yiwei Zuo +3
We present AvatarTex, a high-fidelity facial texture reconstruction framework capable of generating both stylized and photorealistic textures from a single image. Existing methods…
Towards Unified 3D Hair Reconstruction from Single-View Portraits
Yujian Zheng, Yuda Qiu, Leyang Jin +5
Single-view 3D hair reconstruction is challenging, due to the wide range of shape variations among diverse hairstyles. Current state-of-the-art methods are specialized in recoverin…
SphereHead: Stable 3D Full-head Synthesis with Spherical Tri-plane Representation
Heyuan Li, Ce Chen, Tianhao Shi +4
While recent advances in 3D-aware Generative Adversarial Networks (GANs) have aided the development of near-frontal view human face synthesis, the challenge of comprehensively synt…
FashionTex: Controllable Virtual Try-on with Text and Texture
Anran Lin, Nanxuan Zhao, Shuliang Ning +3
Virtual try-on attracts increasing research attention as a promising way for enhancing the user experience for online cloth shopping. Though existing methods can generate impressiv…
Registering Explicit to Implicit: Towards High-Fidelity Garment mesh Reconstruction from Single Images
Heming Zhu, Lingteng Qiu, Yuda Qiu +1
Fueled by the power of deep learning techniques and implicit shape learning, recent advances in single-image human digitalization have reached unprecedented accuracy and could reco…
3DCaricShop: A Dataset and A Baseline Method for Single-view 3D Caricature Face Reconstruction
Yuda Qiu, Xiaojie Xu, Lingteng Qiu +4
Caricature is an artistic representation that deliberately exaggerates the distinctive features of a human face to convey humor or sarcasm. However, reconstructing a 3D caricature…
Learning Inverse Rendering of Faces from Real-world Videos
Yuda Qiu, Zhangyang Xiong, Kai Han +3
In this paper we examine the problem of inverse rendering of real face images. Existing methods decompose a face image into three components (albedo, normal, and illumination) by s…
Learning Mutually Local-global U-nets For High-resolution Retinal Lesion Segmentation in Fundus Images
Zizheng Yan, Xiaoguang Han, Changmiao Wang +3
Diabetic retinopathy is the most important complication of diabetes. Early diagnosis of retinal lesions helps to avoid visual loss or blindness. Due to high-resolution and small-si…
CaricatureShop: Personalized and Photorealistic Caricature Sketching
Xiaoguang Han, Kangcheng Hou, Dong Du +4
In this paper, we propose the first sketching system for interactively personalized and photorealistic face caricaturing. Input an image of a human face, the users can create caric…