Plasticine3D: 3D Non-Rigid Editing with Text Guidance by Multi-View Embedding Optimization
With the help of Score Distillation Sampling (SDS) and the rapid development of neural 3D representations, some methods have been proposed to perform 3D editing such as adding additional geometries, or overwriting textures. However, generalized 3D non-rigid editing task, which requires changing both...
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Zusammenfassung: | With the help of Score Distillation Sampling (SDS) and the rapid development
of neural 3D representations, some methods have been proposed to perform 3D
editing such as adding additional geometries, or overwriting textures. However,
generalized 3D non-rigid editing task, which requires changing both the
structure (posture or composition) and appearance (texture) of the original
object, remains to be challenging in 3D editing field. In this paper, we
propose Plasticine3D, a novel text-guided fine-grained controlled 3D editing
pipeline that can perform 3D non-rigid editing with large structure
deformations. Our work divides the editing process into a geometry editing
stage and a texture editing stage to achieve separate control of structure and
appearance. In order to maintain the details of the original object from
different viewpoints, we propose a Multi-View-Embedding (MVE) Optimization
strategy to ensure that the guidance model learns the features of the original
object from various viewpoints. For the purpose of fine-grained control, we
propose Embedding-Fusion (EF) to blend the original characteristics with the
editing objectives in the embedding space, and control the extent of editing by
adjusting the fusion rate. Furthermore, in order to address the issue of
gradual loss of details during the generation process under high editing
intensity, as well as the problem of insignificant editing effects in some
scenarios, we propose Score Projection Sampling (SPS) as a replacement of score
distillation sampling, which introduces additional optimization phases for
editing target enhancement and original detail maintenance, leading to better
editing quality. Extensive experiments demonstrate the effectiveness of our
method on 3D non-rigid editing tasks |
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DOI: | 10.48550/arxiv.2312.10111 |