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Found 4 papers, 4 papers with code
VIVE3D: Viewpoint-Independent Video Editing using 3D-Aware GANs
Our experiments demonstrate that VIVE3D generates high-fidelity face edits at consistent quality from a range of camera viewpoints which are composited with the original video in a temporally and spatially consistent manner.
InsetGAN for Full-Body Image Generation
Instead of modeling this complex domain with a single GAN, we propose a novel method to combine multiple pretrained GANs, where one GAN generates a global canvas (e. g., human body) and a set of specialized GANs, or insets, focus on different parts (e. g., faces, shoes) that can be seamlessly inserted onto the global canvas.
On the Robustness of Quality Measures for GANs
Finally, we show that the FID can be robustified by simply replacing the standard Inception with a robust Inception.
TileGAN: Synthesis of Large-Scale Non-Homogeneous Textures
We tackle the problem of texture synthesis in the setting where many input images are given and a large-scale output is required.
