5 papers · 1 filter
AvatarVTON: 4D Virtual Try-On for Animatable Avatars
Zicheng Jiang, Jixin Gao, Shengfeng He +5
We propose AvatarVTON, the first 4D virtual try-on framework that generates realistic try-on results from a single in-shop garment image, enabling free pose control, novel-view ren…
Cross-Subject Mind Decoding from Inaccurate Representations
Yangyang Xu, Bangzhen Liu, Wenqi Shao +3
Decoding stimulus images from fMRI signals has advanced with pre-trained generative models. However, existing methods struggle with cross-subject mappings due to cognitive variabil…
HarmonPaint: Harmonized Training-Free Diffusion Inpainting
Ying Li, Xinzhe Li, Yong Du +3
Existing inpainting methods often require extensive retraining or fine-tuning to integrate new content seamlessly, yet they struggle to maintain coherence in both structure and sty…
OmniVTON: Training-Free Universal Virtual Try-On
Zhaotong Yang, Yuhui Li, Shengfeng He +4
Image-based Virtual Try-On (VTON) techniques rely on either supervised in-shop approaches, which ensure high fidelity but struggle with cross-domain generalization, or unsupervised…
Stable Score Distillation
Haiming Zhu, Yangyang Xu, Chenshu Xu +5
Text-guided image and 3D editing have advanced with diffusion-based models, yet methods like Delta Denoising Score often struggle with stability, spatial control, and editing stren…