9 citations · 25 across the 9 of their papers we have counts for
9 papers
EasyCraft: A Robust and Efficient Framework for Automatic Avatar Crafting
Suzhen Wang, Weijie Chen, Wei Zhang +5
Character customization, or 'face crafting,' is a vital feature in role-playing games (RPGs), enhancing player engagement by enabling the creation of personalized avatars. Existing…
StyleTalk++: A Unified Framework for Controlling the Speaking Styles of Talking Heads
Suzhen Wang, Yifeng Ma, Yu Ding +5
Individuals have unique facial expression and head pose styles that reflect their personalized speaking styles. Existing one-shot talking head methods cannot capture such personali…
TalkCLIP: Talking Head Generation with Text-Guided Expressive Speaking Styles
Yifeng Ma, Suzhen Wang, Yu Ding +6
Audio-driven talking head generation has drawn growing attention. To produce talking head videos with desired facial expressions, previous methods rely on extra reference videos to…
StyleTalk: One-shot Talking Head Generation with Controllable Speaking Styles
Yifeng Ma, Suzhen Wang, Zhipeng Hu +5
Different people speak with diverse personalized speaking styles. Although existing one-shot talking head methods have made significant progress in lip sync, natural facial express…
FlowFace: Semantic Flow-guided Shape-aware Face Swapping
Hao Zeng, Wei Zhang, Changjie Fan +7
In this work, we propose a semantic flow-guided two-stage framework for shape-aware face swapping, namely FlowFace. Unlike most previous methods that focus on transferring the sour…
Transformer-based Multimodal Information Fusion for Facial Expression Analysis
Wei Zhang, Feng Qiu, Suzhen Wang +5
Human affective behavior analysis has received much attention in human-computer interaction (HCI). In this paper, we introduce our submission to the CVPR 2022 Competition on Affect…
One-shot Talking Face Generation from Single-speaker Audio-Visual Correlation Learning
Suzhen Wang, Lincheng Li, Yu Ding +1
Audio-driven one-shot talking face generation methods are usually trained on video resources of various persons. However, their created videos often suffer unnatural mouth shapes a…
Audio2Head: Audio-driven One-shot Talking-head Generation with Natural Head Motion
Suzhen Wang, Lincheng Li, Yu Ding +2
We propose an audio-driven talking-head method to generate photo-realistic talking-head videos from a single reference image. In this work, we tackle two key challenges: (i) produc…
Write-a-speaker: Text-based Emotional and Rhythmic Talking-head Generation
Lincheng Li, Suzhen Wang, Zhimeng Zhang +4
In this paper, we propose a novel text-based talking-head video generation framework that synthesizes high-fidelity facial expressions and head motions in accordance with contextua…