06·Research
Academic Papers
Two companion academic papers on applied Gaussian splatting for luxury interiors, one on production-deployment lessons from the benchmark, one (Reflection-Aware 5DGS) on the mirror-and-glass problem. Both drafted; a Tech Communications submission in preparation.
Discover
Why it exists.
The 3DGS research pipeline produced enough evidence to argue something contentious in the field: applied 3D Gaussian Splatting in luxury real-estate visualisation is bottlenecked not by quality but by robustness, and the engine that wins on average PSNR is not the engine that survives the failure modes a brokerage actually encounters.
An academic write-up is the right home for it, the contribution is industry-validated applied work, not theoretical novelty. The paper frames the eval framework, surfaces the heatmap as the central artefact, and argues for failure-mode reporting as a first-class metric in 3DGS benchmarks.
Stack3DGS · Novel-view synthesis · Video diffusion · Research writing
Define
The brief.
Make the case, in an academic paper, that robustness and failure-mode reporting matter more than leaderboard PSNR for applied 3DGS.
Develop
What it took
Skills behind it.
Primary discipline plus the support stack.
Skills demonstrated
- ResearchPrimary
Sole author of two companion academic papers: production-deployment lessons from the benchmark, and Reflection-Aware 5DGS (classified-quadric reflectors for specular interiors).
- 3D & SpatialSecondary
Engine benchmark and scan-difficulty taxonomy from Easy Studio through Extreme Commercial Office.
- AI & Machine LearningSecondary
Novel-view synthesis comparison across diffusion-based and photogrammetric baselines.
- Data PipelinesSupporting
PSNR / SSIM heatmaps and per-engine robustness scoring.
Develop · Build
How it came together.
- 01
Lead with the heatmap, not the average
Submission opens with the PSNR-by-engine × scan heatmap, with failure cells highlighted in red, before the per-engine averages are introduced. Forces the reviewer to confront robustness before they reach for the leaderboard.
Research - 02
Seven scan-difficulty bands as the spine of the eval
Easy Scan-Studio through Extreme Commercial-Office. Each band selected for distinct failure modes, texture sparsity, specularity, scale ambiguity, lighting variance. Reviewers can challenge the band definitions but not the spread of conditions covered.
Research - 03
Reproducibility is the second contribution
The paper ships with the eval harness, the scan-difficulty rubric, and the per-engine launch scripts. The first contribution is the result; the second is the framework anyone else can run on their next engine release.
Data Pipelines
Deliver
What shipped.
Drafted as two companion papers, a Tech Communications submission in preparation. Regardless of where they land, the eval framework is already in production use guiding which 3DGS engine ships behind Splat Viewer for each property type. Writing it up doubled as a forcing function to clean up the engine-by-engine documentation and the failure-mode taxonomy.
Research origin
The paper-to-product thread this project sits inside. The full chain (paper, benchmark, ship) lives on the research index.
- 3D Gaussian SplattingSee thread
Real-time radiance fields applied to luxury real-estate visualisation.
Frames
Selected from the work.
3 frames
01Apartment Floorplan 02Villa Floorplan 03Performance Heatmap