3dgs-code-reviewer
FeaturedReview 3DGS implementation code for correctness, performance bugs, and best practices. Covers CUDA kernels, rendering pipeline, training loop, loss functions. Detects 104 known bug patterns including compression, forensics, SLAM, feed-forward, and method-specific failure patterns. Use when: reviewing 3DGS/Gaussian Splatting CUDA code, debugging rendering artifacts, optimizing 3DGS training pipelines, checking loss function implementations, 代码审查/3DGS调试/性能优化.
Install
Quality Score: 94/100
Skill Content
Details
- Author
- jaccen
- Repository
- jaccen/Awesome-Gaussian-Skills
- Created
- 5 months ago
- Last Updated
- yesterday
- Language
- HTML
- License
- Apache-2.0
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3dgs-training-debugger
Diagnose and fix 3DGS training-time failures: NaN losses, OOM crashes, divergent optimization, floater artifacts, densification failures, hyperparameter sensitivity. Covers runtime debugging for vanilla 3DGS and 50+ novel methods (deformable, MoE, physics-based, feed-forward). Detects 60 runtime failure patterns. Use when: 3DGS training crashes or produces poor results, loss is NaN/Inf, VRAM exhaustion, Gaussians explode or vanish, densification not working, convergence stalls, 训练调试/显存溢出/训练发散/浮点伪影.
3dgs-method-compare
Compare 3D Gaussian Splatting variants across 11 dimensions. Built-in knowledge of 678+ methods across 23 categories. Supports axis-driven fragment loading for efficient context usage. Use when: comparing 3DGS methods or variants, analyzing trade-offs between Gaussian Splatting approaches, generating comparison tables for 3DGS papers, finding the best 3DGS method for a scenario, 检索3DGS方法对比/3D高斯泼溅方法比较.
3dgs-experiment-planner
Design rigorous experiments for 3DGS research papers. Recommends datasets, baselines, metrics, ablation matrices. Targets CVPR/ICCV/ECCV/SIGGRAPH/TVCG. Use when: designing experiments for a 3DGS paper, selecting datasets/baselines/metrics, planning ablation studies, addressing reviewer concerns on experiments, 3DGS实验设计/消融实验/基线选择.