Avatars Grow Legs: Generating Smooth Human Motion from Sparse Tracking Inputs with Diffusion Model
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
IEEE WASPAA
The process of capturing, analyzing and predicting sound fields is finding novel areas of applications in AR/VR. One of the key processes in such applications is to estimate the sound field at locations that differ from the actual measurement points—i.e., the sound field reconstruction. However, it’s a difficult spatial audio processing problem. Though theoretical solutions exist to reconstruct sound fields, they are practically infeasible due to hardware and computational requirements. This paper discusses the implementation of a system for large area sound field recording and reconstruction and proposes an improved sound field reconstruction algorithm. The proposed algorithm introduces a practical improvement in order to overcome implementation issues. In addition, we present a preliminary real-world results on an innovative but highly challenging application.
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
Bilge Acun, Benjamin Lee, Fiodar Kazhamiaka, Kiwan Maeng, Manoj Chakkaravarthy, Udit Gupta, David Brooks, Carole-Jean Wu
Ilkan Esiyok, Pascal Berrang, Katriel Cohn-Gordon, Robert Künnemann