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@@ -6,9 +6,9 @@ tags:
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  - 3d-generation
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  - rectified-flow
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  ---
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- # TripoSG - High-Fidelity 3D Shape Synthesis using Large-Scale Rectified Flow Models
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- TripoSG-scribble is a variant of TripoSG. TripoSG is a state-of-the-art image-to-3D generation foundation model that leverages large-scale rectified flow transformers to produce high-fidelity 3D shapes from single images.
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  ## Model Description
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@@ -20,7 +20,7 @@ TripoSG utilizes a novel architecture combining:
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  - Cross-attention mechanism for image feature condition
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  - 1.5B parameters operating on 2048 latent tokens
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- TripoSG-scribble accepts scribble image and text prompt condition. For inference efficiency, TripoSG-scribble is different from TripoSG in:
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  - TripoSG-scribble is a CFG-distilled model and should be used with CFG=0
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  - TripoSG-scribble is trained with 512 latent tokens
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  - 3d-generation
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  - rectified-flow
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  ---
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+ # TripoSG-scribble - Fast 3D Shape Prototyping with Scribble and Prompt
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+ TripoSG-scribble converts a scribble image and a text prompt to a 3D shape. TripoSG-scribble is a variant of TripoSG. TripoSG is a state-of-the-art image-to-3D generation foundation model that leverages large-scale rectified flow transformers to produce high-fidelity 3D shapes from single images.
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  ## Model Description
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  - Cross-attention mechanism for image feature condition
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  - 1.5B parameters operating on 2048 latent tokens
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+ For inference efficiency, TripoSG-scribble is different from TripoSG in:
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  - TripoSG-scribble is a CFG-distilled model and should be used with CFG=0
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  - TripoSG-scribble is trained with 512 latent tokens
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