London Tower 3D Model

February 5, 2026
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Updated February 10, 2026
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2 min read


Artist Krzysztof Szkoda recently transformed archival photography into an immersive digital experience by creating a 3D gaussian splat of London’s Tower Bridge as it appeared in the 1930s. Unlike traditional radiance field methods that require hundreds of images from various angles, Szkoda utilized a tool called SHARP to reconstruct a volumetric environment from a single historical photograph. The process involves extracting depth and focus data from the original 2D shot to estimate 3D geometry. The resulting scene was integrated into Blender using the KIRI Engine add-on, allowing viewers to move through a sepia-toned, three-dimensional window into the past.

Photo of London Tower Bridge

This project marks a significant shift in how we approach digital heritage and archaeology. While lidar and standard photogrammetry are the gold standards for documenting existing structures, they cannot capture the world as it looked a century ago. By applying gaussian splatting to “monocular” sources such as these single images, researchers and artists can now revive lost landscapes and historical moments that exist only in physical archives. This technique bridges the gap between static history and interactive 3D modeling, offering a new way for museums and educators to visualize urban evolution without needing vintage film footage or multiple perspective shots.

For more information, this workflow highlights the growing connections between artificial intelligence and 3D reconstruction. Szkoda’s use of the SHARP project demonstrates how depth-estimation AI can supplement 3DGS workflows when data is scarce. Additionally, the integration with Blender via the KIRI Engine add-on shows the accessibility of these high-end tools for independent creators. As these technologies mature, the ability to turn any historical photograph into a navigable point cloud or splat will likely become a staple in earth sciences and historical mapping. You can view the full breakdown and the impressive visual results at the link below.

Read More: https://80.lv/articles/3d-gaussian-splat-of-london-s-tower-bridge-during-1930s

Written by Adam Clark. Adam has spent the past 13 years exploring the world from above by using drones, satellites, and mapping tools to better understand our landscapes. Connect with him on LinkedIn: Adam Clark

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SAM Managed geospatial services

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The four stages of 3D Gaussian Splatting reconstruction, visualised as a single progression. A sparse point cloud provides the initial spatial skeleton (left); large overlapping Gaussian primitives are seeded from those points and begin to occupy volume (second); the optimiser densifies and refines those primitives, packing them tighter as the form converges (third); finally, alpha-compositing from the correct viewpoint produces a photorealistic render with no visible primitives remaining (right). The primitives never disappear, they simply become coherent. This is not a surface mesh, not a voxel grid, not a neural network at render time. It is millions of learned ellipsoids, each carrying position, shape, rotation, colour and opacity, composited in depth order at real-time frame rates. Image: Mike Devers / Cr8ive Media

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