Researchers From Princeton and Adobe Propose 3D-FM GAN: A Novel Conditional GAN Framework Designed Specifically For 3D-Controllable Face Manipulation

The development of 3D-controllable portrait synthesis has been significant. However, it is still difficult to precisely control existing face photos in 3D. Even though it is a simple approach, concatenating GAN inversion and a 3D-aware, noise-to-image GAN is ineffective and could result in a glaring decline in editing quality. To close this gap, a team […]

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