Pano2Cloud: Street-View Based Point Cloud for 3D Building Façade Reconstruction

A 2.0 GB collection of data and code supporting a paper on 3D building façade reconstruction. The dataset, authored by Anqi Lin and last updated in May 2026, likely contains street-view imagery and derived point clouds for enhancing 3D models. It includes files in formats such as PY, JPG, LAS, TXT, RAR, XLSX, DOCX, and CSV.

Use Cases

• Training deep learning models for 3D building reconstruction based on the described dual-layer matching method.
• Benchmarking point cloud enhancement algorithms using the provided street-view and point cloud data.
• Developing software tools for photogrammetry and geospatial analysis based on the included code and data formats.

Strengths

• Dataset size is explicitly 2.0 GB, indicating a substantial volume of data.
• Includes associated code (PY files) for reproducibility of the described Pano2Cloud method.
• Released under a permissive CC-BY-4.0 license, facilitating reuse and modification.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for specific modeling tasks.
• Geographic and temporal coverage of the source street-view imagery is not specified.

Provenance

Source

Anqi Lin, via figshare.

Collection Method

Created as supporting material for the academic paper "Pano2Cloud: enhancing street-view based point cloud by a dual-layer deep matching for 3D building façade reconstruction".

Freshness

Last updated 2026-05-26 06:48:11