activity
20182022
most citedPose-Controllable Talking Face Generation by Implicitly Modularized Audio-Visual Representation

24 citations · 106 across the 16 of their papers we have counts for

collaborators

18 papers

cs.CV2022

Masked Lip-Sync Prediction by Audio-Visual Contextual Exploitation in Transformers

Yasheng Sun, Hang Zhou, Kaisiyuan Wang +7

Previous studies have explored generating accurately lip-synced talking faces for arbitrary targets given audio conditions. However, most of them deform or generate the whole facia…

cs.CV202214 cited

Audio-Driven Co-Speech Gesture Video Generation

Xian Liu, Qianyi Wu, Hang Zhou +4

Co-speech gesture is crucial for human-machine interaction and digital entertainment. While previous works mostly map speech audio to human skeletons (e.g., 2D keypoints), directly…

cs.CV202217 cited

Real-time Neural Radiance Talking Portrait Synthesis via Audio-spatial Decomposition

Jiaxiang Tang, Kaisiyuan Wang, Hang Zhou +6

While dynamic Neural Radiance Fields (NeRF) have shown success in high-fidelity 3D modeling of talking portraits, the slow training and inference speed severely obstruct their pote…

cs.CV20221 cited

StyleSwap: Style-Based Generator Empowers Robust Face Swapping

Zhiliang Xu, Hang Zhou, Zhibin Hong +7

Numerous attempts have been made to the task of person-agnostic face swapping given its wide applications. While existing methods mostly rely on tedious network and loss designs, t…

cs.CV2022

Few-Shot Head Swapping in the Wild

Changyong Shu, Hemao Wu, Hang Zhou +7

The head swapping task aims at flawlessly placing a source head onto a target body, which is of great importance to various entertainment scenarios. While face swapping has drawn m…

cs.MM20221 cited

SeCo: Separating Unknown Musical Visual Sounds with Consistency Guidance

Xinchi Zhou, Dongzhan Zhou, Wanli Ouyang +3

Recent years have witnessed the success of deep learning on the visual sound separation task. However, existing works follow similar settings where the training and testing dataset…