Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T14:55:20.012421Z
Paper Citation Record · LEDGER
As of 15 August 2026, this Paper Citation Record lists 98 of 98 outbound references and 0 inbound Pith citation observations for arXiv:2412.11519.
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Pith citing papers itemized under the disclosed page cap.
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A source-named dated measurement, never combined with another source.
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98 of 98 outbound references displayed
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LineArt: A Knowledge-guided Training-free High-quality Appearance Transfer for Design Drawing with Diffusion Model Cross-image attention for zero- shot appearance transfer
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LineArt: A Knowledge-guided Training-free High-quality Appearance Transfer for Design Drawing with Diffusion Model What sketch explainability really means for downstream tasks? In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages 10997–11008, 2024
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LineArt: A Knowledge-guided Training-free High-quality Appearance Transfer for Design Drawing with Diffusion Model Sketch less for more: On-the-fly fine-grained sketch-based image retrieval
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LineArt: A Knowledge-guided Training-free High-quality Appearance Transfer for Design Drawing with Diffusion Model Sketchygan: Towards di- verse and realistic sketch to image synthesis
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LineArt: A Knowledge-guided Training-free High-quality Appearance Transfer for Design Drawing with Diffusion Model Style injec- tion in diffusion: A training-free approach for adapting large- scale diffusion models for style transfer
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LineArt: A Knowledge-guided Training-free High-quality Appearance Transfer for Design Drawing with Diffusion Model Cross- modal latent space alignment for image to avatar translation
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LineArt: A Knowledge-guided Training-free High-quality Appearance Transfer for Design Drawing with Diffusion Model How do humans sketch objects? ACM Transactions on graphics (TOG) , 31 (4):1–10, 2012
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LineArt: A Knowledge-guided Training-free High-quality Appearance Transfer for Design Drawing with Diffusion Model Exploring the structure of a real-time, arbitrary neural artistic stylization network
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LineArt: A Knowledge-guided Training-free High-quality Appearance Transfer for Design Drawing with Diffusion Model Sc-fegan: Face editing gen- erative adversarial network with user’s sketch and color
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Reference 90
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