4 papers
Densemarks: Learning Canonical Embeddings for Human Heads Images via Point Tracks
Dmitrii Pozdeev, Alexey Artemov, Ananta R. Bhattarai +1
We propose DenseMarks - a new learned representation for human heads, enabling high-quality dense correspondences of human head images. For a 2D image of a human head, a Vision Tra…
3DGH: 3D Head Generation with Composable Hair and Face
Chengan He, Junxuan Li, Tobias Kirschstein +7
We present 3DGH, an unconditional generative model for 3D human heads with composable hair and face components. Unlike previous work that entangles the modeling of hair and face, w…
Avat3r: Large Animatable Gaussian Reconstruction Model for High-fidelity 3D Head Avatars
Tobias Kirschstein, Javier Romero, Artem Sevastopolsky +2
Traditionally, creating photo-realistic 3D head avatars requires a studio-level multi-view capture setup and expensive optimization during test-time, limiting the use of digital hu…
GaussianSpeech: Audio-Driven Gaussian Avatars
Shivangi Aneja, Artem Sevastopolsky, Tobias Kirschstein +3
We introduce GaussianSpeech, a novel approach that synthesizes high-fidelity animation sequences of photo-realistic, personalized 3D human head avatars from spoken audio. To captur…