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From One to More: Contextual Part Latents for 3D Generation
Paper • 2507.08772 • Published • 20 -
OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesion
Paper • 2507.06165 • Published • 54 -
SeqTex: Generate Mesh Textures in Video Sequence
Paper • 2507.04285 • Published • 8 -
Ultra3D: Efficient and High-Fidelity 3D Generation with Part Attention
Paper • 2507.17745 • Published • 30
Collections
Discover the best community collections!
Collections including paper arxiv:2507.06165
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LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 35 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 28 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 126 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 23
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From One to More: Contextual Part Latents for 3D Generation
Paper • 2507.08772 • Published • 20 -
OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesion
Paper • 2507.06165 • Published • 54 -
SeqTex: Generate Mesh Textures in Video Sequence
Paper • 2507.04285 • Published • 8 -
Ultra3D: Efficient and High-Fidelity 3D Generation with Part Attention
Paper • 2507.17745 • Published • 30
-
LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 35 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 28 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 126 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 23