Methods › Computer Vision › Generative Adversarial Networks › LipGAN
LipGAN
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
LipGAN is a generative adversarial network for generating realistic talking faces conditioned on translated speech. It employs an adversary that measures the extent of lip synchronization in the frames generated by the generator. The system is capable of handling faces in random poses without the need for realignment to a template pose. LipGAN is a fully self-supervised approach that learns a phoneme-viseme mapping, making it language independent.
Papers archive 2025-07-28
2 shown of 2, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
-
All's well that FID's well? Result quality and metric scores in GAN models for lip-sychronization tasks 28 Dec 2022 · 0 repositories · arXiv:2212.13810
-
Towards Automatic Face-to-Face Translation 1 Mar 2020 · 1 repository · arXiv:2003.00418Syntology ran 2 of 2 samples · 0 unverified
Tasks archive 2025-07-28
5 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Face to Face Translation | 1 |
| Machine Translation | 1 |
| Speech-to-Speech Translation | 1 |
| Translation | 1 |
| Unconstrained Lip-synchronization | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections