111 citations · 136 across the 4 of their papers we have counts for
6 papers
AVTR-1: Open Stack for Real-Time Interactive Avatars
Artem Kravtsov, Dmitrii Ziganshin, Vsevolod Poletaev +4
Talking-head and dyadic models now achieve real-time inference, yet fast motion generation alone does not produce an interactive conversation. A live system must synchronize the mo…
Multi-NeuS: 3D Head Portraits from Single Image with Neural Implicit Functions
Egor Burkov, Ruslan Rakhimov, Aleksandr Safin +2
We present an approach for the reconstruction of textured 3D meshes of human heads from one or few views. Since such few-shot reconstruction is underconstrained, it requires prior…
Neural Head Reenactment with Latent Pose Descriptors
Egor Burkov, Igor Pasechnik, Artur Grigorev +1
We propose a neural head reenactment system, which is driven by a latent pose representation and is capable of predicting the foreground segmentation alongside the RGB image. The l…
Textured Neural Avatars
Aliaksandra Shysheya, Egor Zakharov, Kara-Ali Aliev +9
We present a system for learning full-body neural avatars, i.e. deep networks that produce full-body renderings of a person for varying body pose and camera position. Our system ta…
Learnable Triangulation of Human Pose
Karim Iskakov, Egor Burkov, Victor Lempitsky +1
We present two novel solutions for multi-view 3D human pose estimation based on new learnable triangulation methods that combine 3D information from multiple 2D views. The first (b…
Few-Shot Adversarial Learning of Realistic Neural Talking Head Models
Egor Zakharov, Aliaksandra Shysheya, Egor Burkov +1
Several recent works have shown how highly realistic human head images can be obtained by training convolutional neural networks to generate them. In order to create a personalized…