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Found 5 papers, 1 papers with code
latentSplat: Autoencoding Variational Gaussians for Fast Generalizable 3D Reconstruction
We present latentSplat, a method to predict semantic Gaussians in a 3D latent space that can be splatted and decoded by a light-weight generative 2D architecture.
Neural Point Cloud Diffusion for Disentangled 3D Shape and Appearance Generation
However, none of the existing models enable disentangled generation to control the shape and appearance separately.
Neural Parametric Gaussians for Monocular Non-Rigid Object Reconstruction
However, owing to the ill-posed nature of this problem, there has been no solution that can provide consistent, high-quality novel views from camera positions that are significantly different from the training views.
SimNP: Learning Self-Similarity Priors Between Neural Points
(1) We design the first neural point representation on a category level by utilizing the concept of coherent point clouds.
Updating Embeddings for Dynamic Knowledge Graphs
To utilize information from Knowledge Graphs, many state-of-the-art machine learning approaches use embedding techniques.
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