Get 3D object shape from ImageNet images by using StyleGAN2 generator with Shen
Get 3D object shape from ImageNet images by using StyleGAN2 generator with Shen
Geometry aware 3D generation from in-the-wild images in ImageNet
arXiv paper abstract https://browse.arxiv.org/abs/2402.00225
arXiv PDFpaper https://browse.arxiv.org/pdf/2402.00225.pdf
Generating accurate 3D models is a challenging problem that traditionally requires explicit learning from 3D datasets using supervised learning.
... propose a method for reconstructing 3D geometry from the diverse and unstructured Imagenet dataset without camera pose information.
... use an efficient triplane representation to learn 3D models from 2D images and modify the architecture of the generator backbone based on StyleGAN2 to adapt to the highly diverse dataset.
To prevent mode collapse and improve the training stability on diverse data, ... propose to use multi-view discrimination.
The trained generator can produce class-conditional 3D models as well as renderings from arbitrary viewpoints.
The class-conditional generation results demonstrate significant improvement over the current state-of-the-art method ...
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