AI RESEARCH
Large-Scale High-Quality 3D Gaussian Head Reconstruction from Multi-View Captures
arXiv CS.LG
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ArXi:2605.04035v1 Announce Type: cross We propose HeadsUp, a scalable feed-forward method for reconstructing high-quality 3D Gaussian heads from large-scale multi-camera setups. Our method employs an efficient encoder-decoder architecture that compresses input views into a compact latent representation. This latent representation is then decoded into a set of UV-parameterized 3D Gaussians anchored to a neutral head template. This UV representation decouples the number of 3D Gaussians from the number and resolution of input images, enabling.