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Found 7 papers, 4 papers with code
Coloring the Past: Neural Historical Buildings Reconstruction from Archival Photography
Historical buildings are a treasure and milestone of human cultural heritage.
Erasing the Ephemeral: Joint Camera Refinement and Transient Object Removal for Street View Synthesis
Synthesizing novel views for urban environments is crucial for tasks like autonomous driving and virtual tours.
Enhancing Surface Neural Implicits with Curvature-Guided Sampling and Uncertainty-Augmented Representations
Neural implicits have become popular for representing surfaces because they offer an adaptive resolution and support arbitrary topologies.
High-Quality RGB-D Reconstruction via Multi-View Uncalibrated Photometric Stereo and Gradient-SDF
Fine-detailed reconstructions are in high demand in many applications.
Gradient-SDF: A Semi-Implicit Surface Representation for 3D Reconstruction
We present Gradient-SDF, a novel representation for 3D geometry that combines the advantages of implict and explicit representations.
Dive into Layers: Neural Network Capacity Bounding using Algebraic Geometry
To mathematically prove this, we borrow a tool in topological algebra: Betti numbers to measure the topological geometric complexity of input data and the neural network.
Inferring Super-Resolution Depth from a Moving Light-Source Enhanced RGB-D Sensor: A Variational Approach
A novel approach towards depth map super-resolution using multi-view uncalibrated photometric stereo is presented.
