3dgs-code-reviewer

Troubleshoot 3D Gaussian Splatting training problems with targeted diagnostics for numerical instability, memory exhaustion, convergence failures, and rendering defects. This skill helps identify root causes and apply fixes to get your 3DGS models training smoothly again.

This skill provides methods to reduce 3DGS model size through quantization, pruning, and vector quantization techniques. Optimize your Gaussian Splatting models for faster transmission and lower storage overhead while maintaining visual quality. Ideal for deploying large-scale 3D scene representations in resource-constrained environments.

This skill streamlines research workflows by parsing 3D Gaussian Splatting and NeRF papers to automatically extract key technical metadata. It transforms unstructured academic PDFs into organized, queryable data—eliminating manual note-taking across fragmented sources. Ideal for researchers cataloging methods, tracking innovations, or building comprehensive literature databases.

This skill guides you through adapting NeRF-based approaches into 3D Gaussian Splatting implementations. It provides a methodical framework for translating model architectures, training pipelines, and optimization strategies across these two distinct 3D representation paradigms. Use it to modernize existing NeRF work or explore the technical bridge between classical neural radiance fields and contemporary splatting methods.

Transform CAD meshes into 3D Gaussian Splatting representations and vice versa. This skill bridges traditional mesh-based geometry with modern neural 3D graphics, enabling seamless interoperability between formats for rendering, editing, and visualization tasks.

This skill transforms 3D Gaussian Splatting representations into parametric CAD models, enabling designers and engineers to work with extracted geometry in standard modeling tools. By bridging the gap between neural scene representations and traditional CAD workflows, it streamlines the process of converting spatial data into editable, structured models for further design iteration.