49 citations · 111 across the 20 of their papers we have counts for
13 papers · 1 filter
Guide3D: Create 3D Avatars from Text and Image Guidance
Yukang Cao, Yan-Pei Cao, Kai Han +2
Recently, text-to-image generation has exhibited remarkable advancements, with the ability to produce visually impressive results. In contrast, text-to-3D generation has not yet re…
Sparse3D: Distilling Multiview-Consistent Diffusion for Object Reconstruction from Sparse Views
Zi-Xin Zou, Weihao Cheng, Yan-Pei Cao +3
Reconstructing 3D objects from extremely sparse views is a long-standing and challenging problem. While recent techniques employ image diffusion models for generating plausible ima…
GET3D--: Learning GET3D from Unconstrained Image Collections
Fanghua Yu, Xintao Wang, Zheyuan Li +3
The demand for efficient 3D model generation techniques has grown exponentially, as manual creation of 3D models is time-consuming and requires specialized expertise. While generat…
NOFA: NeRF-based One-shot Facial Avatar Reconstruction
Wangbo Yu, Yanbo Fan, Yong Zhang +8
3D facial avatar reconstruction has been a significant research topic in computer graphics and computer vision, where photo-realistic rendering and flexible controls over poses and…
Neural Point-based Volumetric Avatar: Surface-guided Neural Points for Efficient and Photorealistic Volumetric Head Avatar
Cong Wang, Di Kang, Yan-Pei Cao +3
Rendering photorealistic and dynamically moving human heads is crucial for ensuring a pleasant and immersive experience in AR/VR and video conferencing applications. However, exist…
ID-Pose: Sparse-view Camera Pose Estimation by Inverting Diffusion Models
Weihao Cheng, Yan-Pei Cao, Ying Shan
Given sparse views of a 3D object, estimating their camera poses is a long-standing and intractable problem. Toward this goal, we consider harnessing the pre-trained diffusion mode…
PanoGRF: Generalizable Spherical Radiance Fields for Wide-baseline Panoramas
Zheng Chen, Yan-Pei Cao, Yuan-Chen Guo +3
Achieving an immersive experience enabling users to explore virtual environments with six degrees of freedom (6DoF) is essential for various applications such as virtual reality (V…
SparseGNV: Generating Novel Views of Indoor Scenes with Sparse Input Views
Weihao Cheng, Yan-Pei Cao, Ying Shan
We study to generate novel views of indoor scenes given sparse input views. The challenge is to achieve both photorealism and view consistency. We present SparseGNV: a learning fra…
HOSNeRF: Dynamic Human-Object-Scene Neural Radiance Fields from a Single Video
Jia-Wei Liu, Yan-Pei Cao, Tianyuan Yang +5
We introduce HOSNeRF, a novel 360° free-viewpoint rendering method that reconstructs neural radiance fields for dynamic human-object-scene from a single monocular in-the-wild video…
SurfelNeRF: Neural Surfel Radiance Fields for Online Photorealistic Reconstruction of Indoor Scenes
Yiming Gao, Yan-Pei Cao, Ying Shan
Online reconstructing and rendering of large-scale indoor scenes is a long-standing challenge. SLAM-based methods can reconstruct 3D scene geometry progressively in real time but c…
DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Models
Yukang Cao, Yan-Pei Cao, Kai Han +2
We present DreamAvatar, a text-and-shape guided framework for generating high-quality 3D human avatars with controllable poses. While encouraging results have been reported by rece…
VMesh: Hybrid Volume-Mesh Representation for Efficient View Synthesis
Yuan-Chen Guo, Yan-Pei Cao, Chen Wang +4
With the emergence of neural radiance fields (NeRFs), view synthesis quality has reached an unprecedented level. Compared to traditional mesh-based assets, this volumetric represen…
HRDFuse: Monocular 360°Depth Estimation by Collaboratively Learning Holistic-with-Regional Depth Distributions
Hao Ai, Zidong cao, Yan-pei Cao +2
Depth estimation from a monocular 360° image is a burgeoning problem owing to its holistic sensing of a scene. Recently, some methods, \eg, OmniFusion, have applied the tangent pro…