Albert Mosella-Montoro — accepted AI-conference papers

2026

CGHair: Compact Gaussian Hair Reconstruction with Card Clustering

Haimin Luo, Srinjay Sarkar, Albert Mosella-Montoro, Francisco Vicente Carrasco, Fernando De la Torre

CVPR 2026

We present a compact pipeline for high-fidelity hair reconstruction from multi-view images. While recent 3D Gaussian Splatting (3DGS) methods achieve realistic results, they often require millions of primitives, leading to high storage and rendering costs. Observing that hair exhibits structural and

Cited by 0 Source ↗Scholar ↗

2024

Generalizable Human Gaussians for Sparse View Synthesis

YoungJoong Kwon*, Baole Fang, Yixing Lu, Haoye Dong, Cheng Zhang, Francisco Vicente Carrasco +6

ECCV 2024poster

"Recent progress in neural rendering has brought forth pioneering methods, such as NeRF and Gaussian Splatting, which revolutionize view rendering across various domains like AR/VR, gaming, and content creation. While these methods excel at interpolating within the training data, the challenge of ge…

Cited by 17 Source ↗PDF ↗code ↗Scholar ↗

2022

SkinningNet: Two-Stream Graph Convolutional Neural Network for Skinning Prediction of Synthetic Characters

Albert Mosella-Montoro, Javier Ruiz-Hidalgo

CVPR 2022poster

This work presents SkinningNet, an end-to-end Two-Stream Graph Neural Network architecture that computes skinning weights from an input mesh and its associated skeleton, without making any assumptions on shape class and structure of the provided mesh. Whereas previous methods pre-compute handcrafted…

Cited by 18 PDF ↗Scholar ↗