Abstract Low-Rank Adaptation (LoRA), which updates the dense neural network layers with
pluggable low-rank matrices, is one of the best performed parameter efficient fine-tuning …

Text-to-image diffusion models have proven effective for solving many image editing tasks.
However, the seemingly straightforward task of seamlessly relocating objects within a scene …

The rapid advancement of foundation modelslarge-scale neural networks trained on
diverse, extensive datasetshas revolutionized artificial intelligence, enabling unprecedented …

Style-guided texture generation aims to generate a texture that is harmonious with both the
style of the reference image and the geometry of the input mesh, given a reference style …

This paper introduces UnZipLoRA, a method for decomposing an image into its constituent
subject and style, represented as two distinct LoRAs (Low-Rank Adaptations). Unlike …

Recent large-scale diffusion models generate high-quality images but struggle to learn new,
personalized artistic styles, which limits the creation of unique style templates. Fine-tuning …

Recent advancements in image generation models have enabled personalized image
creation with both user-defined subjects (content) and styles. Prior works achieved …