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Found 5 papers, 1 papers with code
KeyGS: A Keyframe-Centric Gaussian Splatting Method for Monocular Image Sequences
Reconstructing high-quality 3D models from sparse 2D images has garnered significant attention in computer vision.
Partial Distribution Matching via Partial Wasserstein Adversarial Networks
This paper studies the problem of distribution matching (DM), which is a fundamental machine learning problem seeking to robustly align two probability distributions.
Partial Wasserstein Adversarial Network for Non-rigid Point Set Registration
To handle large point sets, we propose a scalable PDM algorithm by utilizing the efficient partial Wasserstein-1 (PW) discrepancy.
Conditional Generative ConvNets for Exemplar-based Texture Synthesis
Given a texture exemplar, the cgCNN model defines a conditional distribution using deep statistics of a ConvNet, and synthesize new textures by sampling from the conditional distribution.
Texture Mixing by Interpolating Deep Statistics via Gaussian Models
More precisely, we first reveal that the statistics used in existing deep models can be unified using a stationary Gaussian scheme.
