3d-aware blending with generative nerfs

H Kim, G Lee, Y Choi, JH Kim… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
Image blending aims to combine multiple images seamlessly. It remains challenging for
existing 2D-based methods, especially when input images are misaligned due to differences …

Style your hair: Latent optimization for pose-invariant hairstyle transfer via local-style-aware hair alignment

T Kim, C Chung, Y Kim, S Park, K Kim… - European Conference on …, 2022 - Springer
Editing hairstyle is unique and challenging due to the complexity and delicacy of hairstyle.
Although recent approaches significantly improved the hair details, these models often …

Stable-hair: Real-world hair transfer via diffusion model

Y Zhang, Q Zhang, Y Song, J Liu - arxiv preprint arxiv:2407.14078, 2024 - arxiv.org
Current hair transfer methods struggle to handle diverse and intricate hairstyles, thus limiting
their applicability in real-world scenarios. In this paper, we propose a novel diffusion-based …

StyleGAN Salon: Multi-View Latent Optimization for Pose-Invariant Hairstyle Transfer

S Khwanmuang, P Phongthawee… - Proceedings of the …, 2023 - openaccess.thecvf.com
Our paper seeks to transfer the hairstyle of a reference image to an input photo for virtual
hair try-on. We target a variety of challenges scenarios, such as transforming a long hairstyle …

HairFastGAN: Realistic and Robust Hair Transfer with a Fast Encoder-Based Approach

M Nikolaev, M Kuznetsov, D Vetrov… - arxiv preprint arxiv …, 2024 - arxiv.org
Our paper addresses the complex task of transferring a hairstyle from a reference image to
an input photo for virtual hair try-on. This task is challenging due to the need to adapt to …