31 citations · 45 across the 11 of their papers we have counts for
12 papers · 1 filter
Phantom: Subject-consistent video generation via cross-modal alignment
Lijie Liu, Tianxiang Ma, Bingchuan Li +6
The continuous development of foundational models for video generation is evolving into various applications, with subject-consistent video generation still in the exploratory stag…
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…
GaFET: Learning Geometry-aware Facial Expression Translation from In-The-Wild Images
Tianxiang Ma, Bingchuan Li, Qian He +2
While current face animation methods can manipulate expressions individually, they suffer from several limitations. The expressions manipulated by some motion-based facial reenactm…
DreamIdentity: Improved Editability for Efficient Face-identity Preserved Image Generation
Zhuowei Chen, Shancheng Fang, Wei Liu +4
While large-scale pre-trained text-to-image models can synthesize diverse and high-quality human-centric images, an intractable problem is how to preserve the face identity for con…
Design Booster: A Text-Guided Diffusion Model for Image Translation with Spatial Layout Preservation
Shiqi Sun, Shancheng Fang, Qian He +1
Diffusion models are able to generate photorealistic images in arbitrary scenes. However, when applying diffusion models to image translation, there exists a trade-off between main…
Semantic 3D-aware Portrait Synthesis and Manipulation Based on Compositional Neural Radiance Field
Tianxiang Ma, Bingchuan Li, Qian He +2
Recently 3D-aware GAN methods with neural radiance field have developed rapidly. However, current methods model the whole image as an overall neural radiance field, which limits th…
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.…
XMP-Font: Self-Supervised Cross-Modality Pre-training for Few-Shot Font Generation
Wei Liu, Fangyue Liu, Fei Ding +2
Generating a new font library is a very labor-intensive and time-consuming job for glyph-rich scripts. Few-shot font generation is thus required, as it requires only a few glyph re…
Region-Aware Face Swapping
Chao Xu, Jiangning Zhang, Miao Hua +3
This paper presents a novel Region-Aware Face Swapping (RAFSwap) network to achieve identity-consistent harmonious high-resolution face generation in a local-global manner: \textbf…
CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP
Zihao Wang, Wei Liu, Qian He +2
Training a text-to-image generator in the general domain (e.g., Dall.e, CogView) requires huge amounts of paired text-image data, which is too expensive to collect. In this paper,…
FaceEraser: Removing Facial Parts for Augmented Reality
Miao Hua, Lijie Liu, Ziyang Cheng +3
Our task is to remove all facial parts (e.g., eyebrows, eyes, mouth and nose), and then impose visual elements onto the ``blank'' face for augmented reality. Conventional object re…
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…