.png){kind=icon}
返回
3D colored object reconstruction from a single view image through diffusion
.png){kind=icon}
PRE
AI
DOI：10.1016/j.eswa.2024.124225.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper we propose a novel 3D colored object reconstruction method from a single view image. Given a reference image, a conditional diffusion probabilistic model is built to reconstruct both a 3D point cloud shape and the corresponding color features at each point, and then images from arbitrary views can be synthesized using a volume rendering technique. The approach involves several sequential steps. First, the reference RGB image is encoded into separate shape and color latent variables. Then, a shape prediction module predicts reverse geometric noise based on the shape latent variable within the diffusion model. Next, a color prediction module predicts color features for each 3D point using information from the color latent variable. Finally, a volume rendering module transforms the generated colored point cloud into 2D image space, facilitating training based solely on a reference image. Experimental results demonstrate that the proposed method achieves competitive performance on colored 3D shape reconstruction and novel view image synthesis.
Keyword:
Shape reconstruction
Colored point cloud
Conditional diffusion probabilistic model
Novel view synthesis
期刊
IF:
7.5
论文数:
3.0W
被引数:
10.2W
机构
引用论文
Different Forms of Vigilance in Response to the Presence of Predators and Conspecifics in a Group‐Living Mammal, the European Rabbit.png)
Ethology
EthologyIF0
PREAI
分享收藏分享收藏An Ultra-Trace Analysis Technique for SF6 Using Gas Chromatography with Negative Ion Chemical Ionization Mass Spectrometry使用气相色谱-负离子化学电离质谱对SF6的超痕量分析技术
OAAI
OAAI分享收藏
SSL-Net: Point-Cloud Generation Network With Self-Supervised LearningSsl-net: 具有自监督学习的点云生成网络IEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏
查看更多内容