VolumeDiffusion: Feed-forward text-to-3D generation with efficient volumetric encoder

This work presents VolumeDiffusion, a novel feed-forward text-to-3D generation framework that directly synthesizes 3D objects from textual descriptions. It bypasses the conventional score distillation loss based or text-to-image-to-3D approaches. To scale up the training data for the diffusion model...

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Bibliographic Details
Main Authors: Zhicong Tang, Shuyang Gu, Chunyu Wang, Ting Zhang, Jianmin Bao, Dong Chen, Baining Guo
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Graphical Models
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Online Access:http://www.sciencedirect.com/science/article/pii/S1524070325000219
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