most citedStyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGAN

4 citations · 7 across the 5 of their papers we have counts for

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cs.CV2023

ToonTalker: Cross-Domain Face Reenactment

Yuan Gong, Yong Zhang, Xiaodong Cun +5

We target cross-domain face reenactment in this paper, i.e., driving a cartoon image with the video of a real person and vice versa. Recently, many works have focused on one-shot t…

cs.CV2023★ 2 cited

NOFA: NeRF-based One-shot Facial Avatar Reconstruction

Wangbo Yu, Yanbo Fan, Yong Zhang +8

3D facial avatar reconstruction has been a significant research topic in computer graphics and computer vision, where photo-realistic rendering and flexible controls over poses and…

cs.CV2023★ 1 cited

High-Fidelity Clothed Avatar Reconstruction from a Single Image

Tingting Liao, Xiaomei Zhang, Yuliang Xiu +7

This paper presents a framework for efficient 3D clothed avatar reconstruction. By combining the advantages of the high accuracy of optimization-based methods and the efficiency of…

cs.CV2022

VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wild

Kun Cheng, Xiaodong Cun, Yong Zhang +6

We present VideoReTalking, a new system to edit the faces of a real-world talking head video according to input audio, producing a high-quality and lip-syncing output video even wi…

cs.CV2022★ 4 cited

StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGAN

Fei Yin, Yong Zhang, Xiaodong Cun +7

One-shot talking face generation aims at synthesizing a high-quality talking face video from an arbitrary portrait image, driven by a video or an audio segment. One challenging qua…