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cs.CV2024

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.CV2024

MosaicFusion: Diffusion Models as Data Augmenters for Large Vocabulary Instance Segmentation

Jiahao Xie, Wei Li, Xiangtai Li +3

We present MosaicFusion, a simple yet effective diffusion-based data augmentation approach for large vocabulary instance segmentation. Our method is training-free and does not rely…

cs.CV2024

OMG-Seg: Is One Model Good Enough For All Segmentation?

Xiangtai Li, Haobo Yuan, Wei Li +6

In this work, we address various segmentation tasks, each traditionally tackled by distinct or partially unified models. We propose OMG-Seg, One Model that is Good enough to effici…

cs.CV2024

MDT-A2G: Exploring Masked Diffusion Transformers for Co-Speech Gesture Generation

Xiaofeng Mao, Zhengkai Jiang, Qilin Wang +7

Recent advancements in the field of Diffusion Transformers have substantially improved the generation of high-quality 2D images, 3D videos, and 3D shapes. However, the effectivenes…

cs.CV2024

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…