A two-stage diffusion framework generates a layout-controllable low-resolution blueprint to guide parallel high-resolution artwork outpainting, achieving 2.4× speedup and improved fidelity over sequential baselines.
Title resolution pending
4 Pith papers cite this work, alongside 109 external citations. Polarity classification is still indexing.
4
Pith papers citing it
109
external citations · external index
fields
cs.CV 4representative citing papers
A decoupled optimization framework with geometry-aware contrastive feature matching transfers both appearance and structure in 3D Gaussian splatting scenes.
Online In-Context Distillation lets small VLMs gain up to 33% performance with as little as 4% teacher annotations by distilling knowledge through dynamic in-context demonstrations at inference.
MythraGen retrieves similar artworks to fine-tune Stable Diffusion via LoRA, producing images that better match text prompts than prior methods on WikiArt.
citing papers explorer
-
High-Resolution Artwork Outpainting with Global Blueprint Guidance and Layout Control
A two-stage diffusion framework generates a layout-controllable low-resolution blueprint to guide parallel high-resolution artwork outpainting, achieving 2.4× speedup and improved fidelity over sequential baselines.
-
Geometry-Aware Style Transfer in 3D Gaussian Splatting
A decoupled optimization framework with geometry-aware contrastive feature matching transfers both appearance and structure in 3D Gaussian splatting scenes.
-
Online In-Context Distillation for Low-Resource Vision Language Models
Online In-Context Distillation lets small VLMs gain up to 33% performance with as little as 4% teacher annotations by distilling knowledge through dynamic in-context demonstrations at inference.
-
MythraGen: Two-Stage Retrieval Augmented Art Generation Framework
MythraGen retrieves similar artworks to fine-tune Stable Diffusion via LoRA, producing images that better match text prompts than prior methods on WikiArt.