11 citations · 19 across the 11 of their papers we have counts for
11 papers
Assembler: Scalable 3D Part Assembly via Anchor Point Diffusion
Wang Zhao, Yan-Pei Cao, Jiale Xu +2
We present Assembler, a scalable and generalizable framework for 3D part assembly that reconstructs complete objects from input part meshes and a reference image. Unlike prior appr…
DI-PCG: Diffusion-based Efficient Inverse Procedural Content Generation for High-quality 3D Asset Creation
Wang Zhao, Yan-Pei Cao, Jiale Xu +2
Procedural Content Generation (PCG) is powerful in creating high-quality 3D contents, yet controlling it to produce desired shapes is difficult and often requires extensive paramet…
Learning High-Quality Navigation and Zooming on Omnidirectional Images in Virtual Reality
Zidong Cao, Zhan Wang, Yexin Liu +4
Viewing omnidirectional images (ODIs) in virtual reality (VR) represents a novel form of media that provides immersive experiences for users to navigate and interact with digital c…
Advances in 3D Generation: A Survey
Xiaoyu Li, Qi Zhang, Di Kang +7
Generating 3D models lies at the core of computer graphics and has been the focus of decades of research. With the emergence of advanced neural representations and generative model…
TIP-Editor: An Accurate 3D Editor Following Both Text-Prompts And Image-Prompts
Jingyu Zhuang, Di Kang, Yan-Pei Cao +3
Text-driven 3D scene editing has gained significant attention owing to its convenience and user-friendliness. However, existing methods still lack accurate control of the specified…
ConTex-Human: Free-View Rendering of Human from a Single Image with Texture-Consistent Synthesis
Xiangjun Gao, Xiaoyu Li, Chaopeng Zhang +4
In this work, we propose a method to address the challenge of rendering a 3D human from a single image in a free-view manner. Some existing approaches could achieve this by using g…
HumanRef: Single Image to 3D Human Generation via Reference-Guided Diffusion
Jingbo Zhang, Xiaoyu Li, Qi Zhang +3
Generating a 3D human model from a single reference image is challenging because it requires inferring textures and geometries in invisible views while maintaining consistency with…
DynVideo-E: Harnessing Dynamic NeRF for Large-Scale Motion- and View-Change Human-Centric Video Editing
Jia-Wei Liu, Yan-Pei Cao, Jay Zhangjie Wu +6
Despite recent progress in diffusion-based video editing, existing methods are limited to short-length videos due to the contradiction between long-range consistency and frame-wise…
HiFi-123: Towards High-fidelity One Image to 3D Content Generation
Wangbo Yu, Li Yuan, Yan-Pei Cao +6
Recent advances in diffusion models have enabled 3D generation from a single image. However, current methods often produce suboptimal results for novel views, with blurred textures…
Anti-Aliased Neural Implicit Surfaces with Encoding Level of Detail
Yiyu Zhuang, Qi Zhang, Ying Feng +6
We present LoD-NeuS, an efficient neural representation for high-frequency geometry detail recovery and anti-aliased novel view rendering. Drawing inspiration from voxel-based repr…
Speech2Lip: High-fidelity Speech to Lip Generation by Learning from a Short Video
Xiuzhe Wu, Pengfei Hu, Yang Wu +6
Synthesizing realistic videos according to a given speech is still an open challenge. Previous works have been plagued by issues such as inaccurate lip shape generation and poor im…