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Found 6 papers, 5 papers with code
DDL-MVS: Depth Discontinuity Learning for MVS Networks
We validate our idea and demonstrate that our strategies can be easily integrated into the existing learning-based MVS pipeline where the reconstruction depends on high-quality depth map estimation.
PSSNet: Planarity-sensible Semantic Segmentation of Large-scale Urban Meshes
The over-segmentation step generates an initial set of mesh segments that capture the planar and non-planar regions of urban scenes.
Reconstructing Compact Building Models from Point Clouds Using Deep Implicit Fields
While three-dimensional (3D) building models play an increasingly pivotal role in many real-world applications, obtaining a compact representation of buildings remains an open problem.
SUM: A Benchmark Dataset of Semantic Urban Meshes
The contributions of this work are threefold: (1) a new benchmark dataset of semantic urban meshes, (2) a novel semi-automatic annotation framework, and (3) an annotation tool for 3D meshes.
The Hessigheim 3D (H3D) Benchmark on Semantic Segmentation of High-Resolution 3D Point Clouds and Textured Meshes from UAV LiDAR and Multi-View-Stereo
Automated semantic segmentation and object detection are of great importance in geospatial data analysis.
CityJSON: A compact and easy-to-use encoding of the CityGML data model
We present CityJSON, a new JSON-based exchange format for the CityGML data model (version 2. 0).
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