Publikation
1D-DiffNPHR: 1D Diffusion Neural Parametric Head Reconstruction using a single image
Pragati Jaiswal; Tewodros Amberbir Habtegebrial; Didier Stricker
In: Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods. International Conference on Pattern Recognition Applications and Methods (ICPRAM-2025), February 23-25, Porto, Portugal, SCITEPRESS (Science and Technology Publications, Lda), 2025.
Zusammenfassung
In the field of 3D reconstruction, recent developments, especially in face reconstruction, have shown considerable promise. Despite these achievements, many of these techniques depend heavily on a large number of input views and are inefficient limiting their practicality. This paper proposes a solution to these challenges by focusing on single-view, full 3D head reconstruction. Our approach leverages a 1D diffusion model in combination with RGB image features and a neural parametric latent representation. Specifically, we train a system to learn latent codes conditioned on features extracted from a single input image. The model directly processes the input image at inference to generate latent codes, which are then decoded into a 3D mesh. Our method achieves high-fidelity reconstructions that outperform state-of-the-art approaches such as 3D Morphable Models, Neural Parametric Head Models, and existing methods for head reconstruction.