UniEdit-Flow presents tuning-free Uni-Inv and Uni-Edit methods for inversion and editing in flow models that achieve accurate reconstruction and robust region-preserving edits across generative models.
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SMFSR achieves state-of-the-art perceptual quality among one-step diffusion-based real-world super-resolution methods by preserving noise-started generation via LR-conditioned SplitMeanFlow and GAN refinement.
Art3D enhances flat-colored 2D illustrations with 3D illusion using pre-trained 2D model features and VLM realism evaluation, then generates 3D, while introducing the Flat-2D benchmark dataset.
citing papers explorer
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UniEdit-Flow: Unleashing Inversion and Editing in the Era of Flow Models
UniEdit-Flow presents tuning-free Uni-Inv and Uni-Edit methods for inversion and editing in flow models that achieve accurate reconstruction and robust region-preserving edits across generative models.
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Noise-Started One-Step Real-World Super-Resolution via LR-Conditioned SplitMeanFlow and GAN Refinement
SMFSR achieves state-of-the-art perceptual quality among one-step diffusion-based real-world super-resolution methods by preserving noise-started generation via LR-conditioned SplitMeanFlow and GAN refinement.
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Art3D: Training-Free 3D Generation from Flat-Colored Illustration
Art3D enhances flat-colored 2D illustrations with 3D illusion using pre-trained 2D model features and VLM realism evaluation, then generates 3D, while introducing the Flat-2D benchmark dataset.