Get 3D shape of object with missing points using text-to-image model with SDS-Complete
Get 3D shape of object with missing points using text-to-image model with SDS-Complete
Point-Cloud Completion with Pretrained Text-to-image Diffusion Models
arXiv paper abstract https://arxiv.org/abs/2306.10533
arXiv PDF paper https://arxiv.org/pdf/2306.10533.pdf
Project page https://sds-complete.github.io
Point-cloud data collected in real-world applications are often incomplete.
... Existing completion approaches rely on datasets of predefined objects to guide the completion of noisy and incomplete, point clouds.
However, these approaches perform poorly when tested on Out-Of-Distribution (OOD) objects, that are poorly represented in the training dataset.
Here ... leverage recent advances in text-guided image generation, which lead to major breakthroughs in text-guided shape generation.
... describe an approach called SDS-Complete that uses a pre-trained text-to-image diffusion model and leverages the text semantics of a given incomplete point cloud of an object, to obtain a complete surface representation.
... find that it effectively reconstructs objects that are absent from common datasets, reducing Chamfer loss by 50% on average compared with current methods ...
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