Synthesized 360 views of Stable Diffusion generated photos with PanoHead

• PanoHead

  1 1,849 4.8 Python

  Code Repository for CVPR 2023 Paper "PanoHead: Geometry-Aware 3D Full-Head Synthesis in 360 degree"

Using the recently released PanoHead: Geometry-Aware 3D Full-Head Synthesis in 360° code https://github.com/sizhean/panohead I had a go with people generated from Stable Diffusion (using DeliberateV2 model). I've not figured out yet how they're generating the camera pose information (in the dataset.json inside dataset folder) so I just used their example images and ran through ControlNet to ensure it was the same camera pose for my images, swapping my image file name for the label in the json array. To get the code running I used WSL Ubuntu and installed Cuda Toolkit 11.3, then created the conda environment from their instructions. I think the code is expecting multiple GPU so I had to change the line device = torch.device('cuda') in all of the main python files in the repo. It could be possible to use the results of this to make a synthetic dataset for dreambooth training of a new coherent person (with a bit of work, the quality needs to be a little higher, maybe running images back through img2img + ControlNet first to clean up).

• eg3d

  10 3,124 0.0 Python
  

It's based on this, which has cats https://github.com/NVlabs/eg3d

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• PanoHead

  1 43 6.4 Python

  Code Repository for CVPR 2023 Paper "PanoHead: Geometry-Aware 3D Full-Head Synthesis in 360 degree" (by hack-mans)

Just added basic version to my fork of the repo, needs some work but currently we still can't generate using a random image yet so I just included their example https://github.com/hack-mans/PanoHead

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