7 papers
Illusion or Integrity? Geometrical Consistency Metric for AIGC Video Quality Evaluation
Yifei Xue, Yuanchen Fei, Hao Zhang +3
Recently, AI-driven video generation has attracted considerable attention. This surge increases the demand for reliable video quality assessment (VQA) metrics to evaluate AI-genera…
KeyframeFace: Language-Driven Facial Animation via Semantic Keyframes
Jingchao Wu, Zejian Kang, Haibo Liu +2
Facial animation is a core component for creating digital characters in Computer Graphics (CG) industry. A typical production workflow relies on sparse, semantically meaningful key…
AudioFace: Language-Assisted Speech-Driven Facial Animation with Multimodal Language Models
Kai Zheng, Zejian Kang, Rui Mao +4
Speech-driven facial animation requires accurate correspondence between acoustic signals and facial motion, especially for articulation-related mouth movements. However, directly m…
SuperFace: Preference-Aligned Facial Expression Estimation Beyond Pseudo Supervision
Zejian Kang, Xuanyang Xu, Wentao Yang +6
Accurate facial estimation is crucial for realistic digital human animation, and ARKit blendshape coefficients offer an interpretable representation by mapping facial motions to se…
Exploring the Role of Synthetic Data Augmentation in Controllable Human-Centric Video Generation
Yuanchen Fei, Yude Zou, Zejian Kang +3
Controllable human video generation aims to produce realistic videos of humans with explicitly guided motions and appearances,serving as a foundation for digital humans, animation,…
SemanticFace: Semantic Facial Action Estimation via Semantic Distillation in Interpretable Space
Zejian Kang, Kai Zheng, Yuanchen Fei +3
Facial action estimation from a single image is often formulated as predicting or fitting parameters in compact expression spaces, which lack explicit semantic interpretability. Ho…