2 citations · 4 across the 11 of their papers we have counts for
12 papers
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…
ViSA: 3D-Aware Video Shading for Real-Time Upper-Body Avatar Creation
Fan Yang, Heyuan Li, Peihao Li +9
Generating high-fidelity upper-body 3D avatars from one-shot input image remains a significant challenge. Current 3D avatar generation methods, which rely on large reconstruction m…
HyPlaneHead: Rethinking Tri-plane-like Representations in Full-Head Image Synthesis
Heyuan Li, Kenkun Liu, Lingteng Qiu +4
Tri-plane-like representations have been widely adopted in 3D-aware GANs for head image synthesis and other 3D object/scene modeling tasks due to their efficiency. However, queryin…
LHM++: An Efficient Large Human Reconstruction Model for Pose-free Images to 3D
Lingteng Qiu, Peihao Li, Heyuan Li +9
Reconstructing animatable 3D humans from casually captured images of articulated subjects without camera or pose information is highly practical but remains challenging due to view…
MCMat: Multiview-Consistent and Physically Accurate PBR Material Generation
Shenhao Zhu, Lingteng Qiu, Xiaodong Gu +11
Existing 2D methods utilize UNet-based diffusion models to generate multi-view physically-based rendering (PBR) maps but struggle with multi-view inconsistency, while some 3D metho…
CT4D: Consistent Text-to-4D Generation with Animatable Meshes
Ce Chen, Shaoli Huang, Xuelin Chen +4
Text-to-4D generation has recently been demonstrated viable by integrating a 2D image diffusion model with a video diffusion model. However, existing models tend to produce results…
DreamDissector: Learning Disentangled Text-to-3D Generation from 2D Diffusion Priors
Zizheng Yan, Jiapeng Zhou, Fanpeng Meng +6
Text-to-3D generation has recently seen significant progress. To enhance its practicality in real-world applications, it is crucial to generate multiple independent objects with in…
StableNormal: Reducing Diffusion Variance for Stable and Sharp Normal
Chongjie Ye, Lingteng Qiu, Xiaodong Gu +6
This work addresses the challenge of high-quality surface normal estimation from monocular colored inputs (i.e., images and videos), a field which has recently been revolutionized…
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…
IPoD: Implicit Field Learning with Point Diffusion for Generalizable 3D Object Reconstruction from Single RGB-D Images
Yushuang Wu, Luyue Shi, Junhao Cai +6
Generalizable 3D object reconstruction from single-view RGB-D images remains a challenging task, particularly with real-world data. Current state-of-the-art methods develop Transfo…
RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3D
Lingteng Qiu, Guanying Chen, Xiaodong Gu +7
Lifting 2D diffusion for 3D generation is a challenging problem due to the lack of geometric prior and the complex entanglement of materials and lighting in natural images. Existin…
SAMPro3D: Locating SAM Prompts in 3D for Zero-Shot Instance Segmentation
Mutian Xu, Xingyilang Yin, Lingteng Qiu +3
We introduce SAMPro3D for zero-shot instance segmentation of 3D scenes. Given the 3D point cloud and multiple posed RGB-D frames of 3D scenes, our approach segments 3D instances by…