We learn to generate photo-realistic 3D heads only from training on 2D images. In contrast to existing works such as EG3D, we leverage the efficient rasterization of 3D Gaussians, thus mitigating the need for any 2D super-resolution networks.
-> enforcing view consistency.
We learn to generate photo-realistic 3D heads only from training on 2D images. In contrast to existing works such as EG3D, we leverage the efficient rasterization of 3D Gaussians, thus mitigating the need for any 2D super-resolution networks.
-> enforcing view consistency.
I will present GGHead next week at SIGGRAPH Asia in Tokyo! Swing by in the Gaussian Humans session if you are interested.
Also, we have released the training code now 🎉
Check it out: github.com/tobias-kirsc...
I will present GGHead next week at SIGGRAPH Asia in Tokyo! Swing by in the Gaussian Humans session if you are interested.
Also, we have released the training code now 🎉
Check it out: github.com/tobias-kirsc...