Summary of Ultraman: Single Image 3d Human Reconstruction with Ultra Speed and Detail, by Mingjin Chen et al.
Ultraman: Single Image 3D Human Reconstruction with Ultra Speed and Detail
by Mingjin Chen, Junhao Chen, Xiaojun Ye, Huan-ang Gao, Xiaoxue Chen, Zhaoxin Fan, Hao Zhao
First submitted to arxiv on: 18 Mar 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Image and Video Processing (eess.IV)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a new method called Ultraman for fast reconstruction of textured 3D human models from a single image. The approach is divided into three parts: geometric reconstruction, texture generation, and texture mapping. The proposed method, Ultraman, significantly improves the reconstruction speed and accuracy while preserving high-quality texture details. It outperforms state-of-the-art methods in terms of human rendering quality and speed. The paper presents a set of new frameworks for human reconstruction, which includes mesh reconstruction, multi-view consistent image generation, and novel texture mapping. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about creating 3D models of humans from just one picture. It’s a challenge because previous methods are slow and don’t capture the details well. The researchers came up with a new way called Ultraman that’s much faster and more accurate. They broke it down into three steps: figuring out the shape, generating textures, and making sure everything looks good. It worked really well on lots of different datasets and was even better than other methods. The code and data will be shared publicly. |
Keywords
» Artificial intelligence » Image generation
