Pshuman : Reconstruct realistic 3D human models from a single image.

Pshuman

3D Modeling AI Model #3D Reconstruction #Human Models #Image Generation #Artificial Intelligence #Computer Vision Standard Picks Open Source

Overview :

PSHuman is an innovative framework that utilizes multi-view diffusion models and explicit reconstruction techniques to reconstruct realistic 3D human models from a single image. Its significance lies in its ability to handle complex self-occlusion issues and avoid geometric distortions in the generated facial details. PSHuman achieves richly detailed new perspective generation while maintaining identity features by jointly modeling global body shapes and local facial characteristics with cross-scale diffusion models. Additionally, PSHuman enhances cross-view body shape consistency under different human postures using physical priors provided by parameterized models like SMPL-X. Key advantages of PSHuman include rich geometric details, high texture fidelity, and strong generalization capability.

Target Users :

The target audience includes 3D modelers, game developers, animators, and professionals in the virtual reality field. The realistic 3D human model reconstruction technology offered by PSHuman helps them create high-quality 3D content quickly and efficiently, whether it's for game character design, animation production, or virtual reality experiences.

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Use Cases

Example 1: A game developer quickly generates realistic game character models using PSHuman.

Example 2: An animator utilizes PSHuman technology to create high-precision 3D character models for animated films.

Example 3: A virtual reality company employs PSHuman technology to create authentic virtual characters for VR experiences.

Features

? Single Image 3D Human Reconstruction: Reconstruct realistic 3D human models using a single image.

? Cross-Scale Multi-View Diffusion: Generate richly detailed new perspectives by jointly modeling global body shapes and local facial features.

? Explicit Reconstruction Techniques: Restore authentic textured human meshes using multi-view normal and color images through differentiable rasterization techniques.

? Body Posture Consistency: Enhance cross-view body shape consistency under various human postures using physical priors from parameterized models like SMPL-X.

? Highly Realistic Textures: Extensive experimental results and quantitative assessments on datasets such as CAPE and THuman2.1 demonstrate PSHuman's advantages in geometric detail, texture fidelity, and generalization capability.

? Strong Versatility: PSHuman is suitable not only for reconstructing 3D models of real people but also for handling 3D reconstructions of non-real characters, such as anime figures.

How to Use

1. Prepare a full-body image of a person.

2. Use the PSHuman framework to input the full-body image and the predicted SMPL-X model.

3. Generate six-view global full-body images and localized facial images using the multi-view image diffusion model.

4. Utilize the explicit human sculpting technique initialized by SMPLX, and deform and reconstruct the SMPL-X model using the generated normal and color maps.

5. Optimize the model to match the input image using differentiable rasterization techniques.

6. Generate the final realistic 3D human model.