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README.md
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@@ -16,7 +16,11 @@ The LDM3D model was proposed in ["LDM3D: Latent Diffusion Model for 3D"](https:/
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LDM3D got accepted to [CVPRW'23]([https://aaai.org/Conferences/AAAI-23/](https://cvpr2023.thecvf.com/)).
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This checkpoint finetunes the previous [ldm3d-4c](https://huggingface.co/Intel/ldm3d-4c) on 2 panoramic-images datasets:
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A demo using this checkpoint has been open sourced in [this space](https://huggingface.co/spaces/Intel/ldm3d)
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LDM3D got accepted to [CVPRW'23]([https://aaai.org/Conferences/AAAI-23/](https://cvpr2023.thecvf.com/)).
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This checkpoint finetunes the previous [ldm3d-4c](https://huggingface.co/Intel/ldm3d-4c) on 2 panoramic-images datasets:
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- [polyhaven](https://polyhaven.com/): 585 images for the training set, 66 images for the validation set
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- [ihdri](https://www.ihdri.com/hdri-skies-outdoor/): 57 outdoor images for the training set, 7 outdoor images for the validation set.
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These datasets were augmented using [Text2Light](https://frozenburning.github.io/projects/text2light/) to create a dataset containing 13852 training samples and 1606 validation samples.
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In order to generate the depth map of those samples, we used [DPT-large](https://github.com/isl-org/MiDaS) and to generate the caption we used [BLIP-2](https://huggingface.co/docs/transformers/main/model_doc/blip-2)
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A demo using this checkpoint has been open sourced in [this space](https://huggingface.co/spaces/Intel/ldm3d)
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