most citedA Generalist FaceX via Learning Unified Facial Representation

2 citations · 5 across the 4 of their papers we have counts for

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cs.CV20241 cited

HiFiVFS: High Fidelity Video Face Swapping

Xu Chen, Keke He, Junwei Zhu +3

Face swapping aims to generate results that combine the identity from the source with attributes from the target. Existing methods primarily focus on image-based face swapping. Whe…

cs.CV2024

ArtWeaver: Advanced Dynamic Style Integration via Diffusion Model

Chengming Xu, Kai Hu, Qilin Wang +5

Stylized Text-to-Image Generation (STIG) aims to generate images from text prompts and style reference images. In this paper, we present ArtWeaver, a novel framework that leverages…

cs.CV20241 cited

Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control

Yue Han, Junwei Zhu, Keke He +7

Current face reenactment and swapping methods mainly rely on GAN frameworks, but recent focus has shifted to pre-trained diffusion models for their superior generation capabilities…

cs.CV20241 cited

DiffFAE: Advancing High-fidelity One-shot Facial Appearance Editing with Space-sensitive Customization and Semantic Preservation

Qilin Wang, Jiangning Zhang, Chengming Xu +7

Facial Appearance Editing (FAE) aims to modify physical attributes, such as pose, expression and lighting, of human facial images while preserving attributes like identity and back…

cs.CV20232 cited

A Generalist FaceX via Learning Unified Facial Representation

Yue Han, Jiangning Zhang, Junwei Zhu +7

This work presents FaceX framework, a novel facial generalist model capable of handling diverse facial tasks simultaneously. To achieve this goal, we initially formulate a unified…