Introduces geodesic flow matching on a Riemannian degradation manifold to generalize linear flow matching for blind image restoration.
Lbm: Latent bridge match- ing for fast image-to-image translation
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
fields
cs.CV 4years
2026 4verdicts
UNVERDICTED 4representative citing papers
LiveMoments restores reselected key photos in Live Photos via reference-guided diffusion and motion alignment, yielding higher perceptual quality and fidelity than prior methods especially under fast motion.
Contrast-X benchmark and FlowMI model enable synthesis of contrast-enhanced images from arbitrary non-contrast modality inputs using multi-modal flow matching.
RenderFlow replaces iterative diffusion with flow matching for deterministic single-step neural rendering that achieves near real-time photorealistic quality and extends to inverse rendering via an adapter module.
citing papers explorer
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Geodesic Flow Matching on a Riemannian Degradation Manifold for Blind Image Restoration
Introduces geodesic flow matching on a Riemannian degradation manifold to generalize linear flow matching for blind image restoration.
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LiveMoments: Reselected Key Photo Restoration in Live Photos via Reference-guided Diffusion
LiveMoments restores reselected key photos in Live Photos via reference-guided diffusion and motion alignment, yielding higher perceptual quality and fidelity than prior methods especially under fast motion.
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Contrast-X: A Multi-Modal Contrast Image Synthesis Benchmark and Universal Modality Flow Matching
Contrast-X benchmark and FlowMI model enable synthesis of contrast-enhanced images from arbitrary non-contrast modality inputs using multi-modal flow matching.
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RenderFlow: Single-Step Neural Rendering via Flow Matching
RenderFlow replaces iterative diffusion with flow matching for deterministic single-step neural rendering that achieves near real-time photorealistic quality and extends to inverse rendering via an adapter module.