5 citations · 5 across the 3 of their papers we have counts for
4 papers
GeoAvatar: Adaptive Geometrical Gaussian Splatting for 3D Head Avatar
SeungJun Moon, Hah Min Lew, Seungeun Lee +2
Despite recent progress in 3D head avatar generation, balancing identity preservation, i.e., reconstruction, with novel poses and expressions, i.e., animation, remains a challenge.…
EPSilon: Efficient Point Sampling for Lightening of Hybrid-based 3D Avatar Generation
Seungjun Moon, Sangjoon Yu, Gyeong-Moon Park
The rapid advancement of neural radiance fields (NeRF) has paved the way to generate animatable human avatars from a monocular video. However, the sole usage of NeRF suffers from a…
Generative Unlearning for Any Identity
Juwon Seo, Sung-Hoon Lee, Tae-Young Lee +2
Recent advances in generative models trained on large-scale datasets have made it possible to synthesize high-quality samples across various domains. Moreover, the emergence of str…
WINE: Wavelet-Guided GAN Inversion and Editing for High-Fidelity Refinement
Chaewon Kim, Seung-Jun Moon, Gyeong-Moon Park
Recent advanced GAN inversion models aim to convey high-fidelity information from original images to generators through methods using generator tuning or high-dimensional feature l…