Text-to-Face Generation
4 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Text-to-Face Generation
Most implemented papers
Text2FaceGAN: Face Generation from Fine Grained Textual Descriptions
We then model the highly multi-modal problem of text to face generation as learning the conditional distribution of faces (conditioned on text) in same latent space.
Parallel and High-Fidelity Text-to-Lip Generation
However, the AR decoding manner generates current lip frame conditioned on frames generated previously, which inherently hinders the inference speed, and also has a detrimental effect on the quality of generated lip frames due to error propagation.
AI-generated characters for supporting personalized learning and well-being
Advancements in machine learning have recently enabled the hyper-realistic synthesis of prose, images, audio and video data, in what is referred to as artificial intelligence (AI)-generated media.
Unite and Conquer: Plug & Play Multi-Modal Synthesis using Diffusion Models
We also introduce a novel reliability parameter that allows using different off-the-shelf diffusion models trained across various datasets during sampling time alone to guide it to the desired outcome satisfying multiple constraints.