5 papers
MAST: Mask-Guided Attention Mass Allocation for Training-Free Multi-Style Transfer
Dongkyung Kang, Jaeyeon Hwang, Junseo Park +6
Style transfer aims to render a content image with the visual characteristics of a reference style while preserving its underlying semantic layout and structural geometry. While re…
ART-VITON: Measurement-Guided Latent Diffusion for Artifact-Free Virtual Try-On
Junseo Park, Hyeryung Jang
Virtual try-on (VITON) aims to generate realistic images of a person wearing a target garment, requiring precise garment alignment in try-on regions and faithful preservation of id…
PQCAD-DM: Progressive Quantization and Calibration-Assisted Distillation for Extremely Efficient Diffusion Model
Beomseok Ko, Hyeryung Jang
Diffusion models excel in image generation but are computational and resource-intensive due to their reliance on iterative Markov chain processes, leading to error accumulation and…
I2AM: Interpreting Image-to-Image Latent Diffusion Models via Bi-Attribution Maps
Junseo Park, Hyeryung Jang
Large-scale diffusion models have made significant advances in image generation, particularly through cross-attention mechanisms. While cross-attention has been well-studied in tex…
StyleForge: Enhancing Text-to-Image Synthesis for Any Artistic Styles with Dual Binding
Junseo Park, Beomseok Ko, Hyeryung Jang
Recent advancements in text-to-image models, such as Stable Diffusion, have showcased their ability to create visual images from natural language prompts. However, existing methods…