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.
Easyoutpainter: One step image outpainting with both continu- ous multiple and resolution
2 Pith papers cite this work, alongside 2 external citations. Polarity classification is still indexing.
2
Pith papers citing it
2
external citations · external index
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 2years
2026 2roles
background 1polarities
background 1representative citing papers
Kernel interpolation with a constant multiplier scales convolution and fully-connected layers in neural networks to higher resolutions or dimensions without training, producing competitive results on Stable Diffusion and other models.
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.
-
Supersampling Stable Diffusion and Beyond: A Seamless, Training-Free Approach for Scaling Neural Networks Using Common Interpolation Methods
Kernel interpolation with a constant multiplier scales convolution and fully-connected layers in neural networks to higher resolutions or dimensions without training, producing competitive results on Stable Diffusion and other models.