Rectified flow learns straight-path neural ODEs for distribution transport, yielding efficient generative models and domain transfers that work well even with a single simulation step.
Generative adversarial nets
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Cross-attention control in text-conditioned models enables localized and global image edits by editing only the input text prompt.
A diffusion model variant that adds structured non-zero-mean noise via modified forward/reverse processes, yielding an ELBO loss analogous to offset noise but with time-dependent coefficients, and showing gains on synthetic high-dimensional data.
Hunyuan3D 2.0 scales flow-based diffusion transformers and texture synthesis models to generate high-resolution textured 3D assets that outperform prior state-of-the-art in geometry, alignment, and texture quality.
citing papers explorer
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Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
Rectified flow learns straight-path neural ODEs for distribution transport, yielding efficient generative models and domain transfers that work well even with a single simulation step.
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Prompt-to-Prompt Image Editing with Cross Attention Control
Cross-attention control in text-conditioned models enables localized and global image edits by editing only the input text prompt.
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A Probabilistic Formulation of Offset Noise in Diffusion Models
A diffusion model variant that adds structured non-zero-mean noise via modified forward/reverse processes, yielding an ELBO loss analogous to offset noise but with time-dependent coefficients, and showing gains on synthetic high-dimensional data.
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Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation
Hunyuan3D 2.0 scales flow-based diffusion transformers and texture synthesis models to generate high-resolution textured 3D assets that outperform prior state-of-the-art in geometry, alignment, and texture quality.