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Recent text-to-3D generation methods achieve impressive 3D content creationcapacity thanks to the advances in image diffusion models and optimizingstrategies. However, current methods struggle to generate correct 3D contentfor a complex prompt in semantics, i.e., a prompt describing multipleinteracted objects binding with different attributes. In this work, we proposea general framework named Progressive3D, which decomposes the entire generationinto a series of locally progressive editing steps to create precise 3D contentfor complex prompts, and we constrain the content change to only occur inregions determined by user-defined region prompts in each editing step.Furthermore, we propose an overlapped semantic component suppression techniqueto encourage the optimization process to focus more on the semantic differencesbetween prompts. Extensive experiments demonstrate that the proposedProgressive3D framework generates precise 3D content for prompts with complexsemantics and is general for various text-to-3D methods driven by different 3Drepresentations.

Progressive3D: Progressively Local Editing for Text-to-3D Content Creation with Complex Semantic Prompts