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DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape Generation
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site name
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updated
2026-03-06 09:22:03
raw text
DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape Generation DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape Generation Shentong Mo 1 , Enze Xie 2 , Ruihang Chu 3 , Lewei Yao 2 , Lanqing Hong 2 , Matthias Nießner 4 , Zhenguo Li 2 1 MBZUAI, 2 Huawei Noah's Ark Lab, 3 CUHK, 4 TUM description Paper description Code Your browser does not support the video tag. We propose DiT-3D, a novel plain Diffusion Transformer for high-fidelity and diverse 3D shape generation , which can directly operate the denoising process on voxelized point clouds. Your browser does not support the video tag. Our DiT-3D takes voxelized point clouds as input, and a patchification operator is used to generate token-level patch embeddings, where 3D positional embeddings are added together. Then, multiple transformer blocks based on 3D window attention extract point-voxel r...
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