4 citations · 9 across the 7 of their papers we have counts for
7 papers
DreamID: High-Fidelity and Fast diffusion-based Face Swapping via Triplet ID Group Learning
Fulong Ye, Miao Hua, Pengze Zhang +5
In this paper, we introduce DreamID, a diffusion-based face swapping model that achieves high levels of ID similarity, attribute preservation, image fidelity, and fast inference sp…
Customize Your Own Paired Data via Few-shot Way
Jinshu Chen, Bingchuan Li, Miao Hua +2
Existing solutions to image editing tasks suffer from several issues. Though achieving remarkably satisfying generated results, some supervised methods require huge amounts of pair…
DreamTuner: Single Image is Enough for Subject-Driven Generation
Miao Hua, Jiawei Liu, Fei Ding +3
Diffusion-based models have demonstrated impressive capabilities for text-to-image generation and are expected for personalized applications of subject-driven generation, which req…
CFFT-GAN: Cross-domain Feature Fusion Transformer for Exemplar-based Image Translation
Tianxiang Ma, Bingchuan Li, Wei Liu +3
Exemplar-based image translation refers to the task of generating images with the desired style, while conditioning on certain input image. Most of the current methods learn the co…
ReGANIE: Rectifying GAN Inversion Errors for Accurate Real Image Editing
Bingchuan Li, Tianxiang Ma, Peng Zhang +4
The StyleGAN family succeed in high-fidelity image generation and allow for flexible and plausible editing of generated images by manipulating the semantic-rich latent style space.…
HS-Diffusion: Semantic-Mixing Diffusion for Head Swapping
Qinghe Wang, Lijie Liu, Miao Hua +5
Image-based head swapping task aims to stitch a source head to another source body flawlessly. This seldom-studied task faces two major challenges: 1) Preserving the head and body…
DyStyle: Dynamic Neural Network for Multi-Attribute-Conditioned Style Editing
Bingchuan Li, Shaofei Cai, Wei Liu +4
The semantic controllability of StyleGAN is enhanced by unremitting research. Although the existing weak supervision methods work well in manipulating the style codes along one att…