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Zejun Ma

59 papers hereh-index 212.1k citations88 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author26
  • last author33

Across the 59 of 59 papers where every author was matched, so the position is known.

fields
  • cs.CL19
  • eess.AS18
  • cs.SD15
  • cs.CV4
  • cs.LG2
  • cs.IR1
same name
  • Zejun Ma — 17 papers, h 15
  • Zejun Ma — 7 papers, h 6
  • Zejun Ma — 1 paper, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172023
most citedTowards Realistic Visual Dubbing with Heterogeneous Sources

34 citations · 195 across the 59 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2023

Ada-TTA: Towards Adaptive High-Quality Text-to-Talking Avatar Synthesis

Zhenhui Ye, Ziyue Jiang, Yi Ren +5

We are interested in a novel task, namely low-resource text-to-talking avatar. Given only a few-minute-long talking person video with the audio track as the training data and arbit…

cs.CV2023★ 5 cited

GeneFace++: Generalized and Stable Real-Time Audio-Driven 3D Talking Face Generation

Zhenhui Ye, Jinzheng He, Ziyue Jiang +7

Generating talking person portraits with arbitrary speech audio is a crucial problem in the field of digital human and metaverse. A modern talking face generation method is expecte…

cs.CV2022★ 34 cited

Towards Realistic Visual Dubbing with Heterogeneous Sources

Tianyi Xie, Liucheng Liao, Cheng Bi +7

The task of few-shot visual dubbing focuses on synchronizing the lip movements with arbitrary speech input for any talking head video. Albeit moderate improvements in current appro…

cs.CV2021

Towards Using Clothes Style Transfer for Scenario-aware Person Video Generation

Jingning Xu, Benlai Tang, Mingjie Wang +4

Clothes style transfer for person video generation is a challenging task, due to drastic variations of intra-person appearance and video scenarios. To tackle this problem, most rec…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.