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

4 citations · 4 across the 2 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

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

Efficient Text-Guided 3D-Aware Portrait Generation with Score Distillation Sampling on Distribution

Yiji Cheng, Fei Yin, Xiaoke Huang +5

Text-to-3D is an emerging task that allows users to create 3D content with infinite possibilities. Existing works tackle the problem by optimizing a 3D representation with guidance…

cs.CV2023

Accelerating Diffusion Models for Inverse Problems through Shortcut Sampling

Gongye Liu, Haoze Sun, Jiayi Li +2

Diffusion models have recently demonstrated an impressive ability to address inverse problems in an unsupervised manner. While existing methods primarily focus on modifying the pos…

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.CV20224 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…