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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