20 citations · 36 across the 3 of their papers we have counts for
7 papers
Bringing Diversity from Diffusion Models to Semantic-Guided Face Asset Generation
Yunxuan Cai, Sitao Xiang, Zongjian Li +2
Digital modeling and reconstruction of human faces serve various applications. However, its availability is often hindered by the requirements of data capturing devices, manual lab…
DisUnknown: Distilling Unknown Factors for Disentanglement Learning
Sitao Xiang, Yuming Gu, Pengda Xiang +4
Disentangling data into interpretable and independent factors is critical for controllable generation tasks. With the availability of labeled data, supervision can help enforce the…
Revisiting the Continuity of Rotation Representations in Neural Networks
Sitao Xiang, Hao Li
In this paper, we provide some careful analysis of certain pathological behavior of Euler angles and unit quaternions encountered in previous works related to rotation representati…
Generative Tweening: Long-term Inbetweening of 3D Human Motions
Yi Zhou, Jingwan Lu, Connelly Barnes +3
The ability to generate complex and realistic human body animations at scale, while following specific artistic constraints, has been a fundamental goal for the game and animation…
One-Shot Identity-Preserving Portrait Reenactment
Sitao Xiang, Yuming Gu, Pengda Xiang +4
We present a deep learning-based framework for portrait reenactment from a single picture of a target (one-shot) and a video of a driving subject. Existing facial reenactment metho…
Disentangling Style and Content in Anime Illustrations
Sitao Xiang, Hao Li
Existing methods for AI-generated artworks still struggle with generating high-quality stylized content, where high-level semantics are preserved, or separating fine-grained styles…