Awesome Gaussian Skills
The Most Comprehensive 3D Gaussian Splatting Catalog — 819+ Methods, 23 Categories, Interactive Explorer
You shouldn't search 20 repos for 3DGS papers. This is the only one you need.
Why This Repo?
Other awesome lists give you paper titles. We give you paper titles + an AI toolkit that makes you faster.
| What You Need | Other Lists | This Repo |
|---|---|---|
| Browse papers | Static markdown table | Interactive explorer: search, filter, sort |
| Compare methods | Open 2 papers side by side | 10+ dimension auto-comparison |
| Avoid code bugs | Discover after submission | 104 known bug pattern detection |
| Design experiments | Guess baselines & ablations | Venue-tailored experiment plan |
| NeRF → 3DGS | Trial-and-error porting | Step-by-step migration guide |
| CAD ↔ 3DGS | No coverage | 40+ method conversion pipeline |
| Patent filing | Manual from scratch | Auto-generated claims & specs |
Live Demo
Try the Interactive Method Explorer →
Search 819+ Methods instantly, filter by category, sort by citations, click any method card for details.
📖 Online Book: Spatial & Embodied Intelligence (New!)
** NEW (Jul 2026)** — A full open-source technical book, built around 3D Gaussian Splatting as the spine and weaving together spatial intelligence and embodied intelligence into one closed loop: representation → perception → planning → action.
Core formula (echoing Agent = LLM + Context + Tools):
Embodied Agent = Spatial Representation × Perception × Planning × Action
What's inside — 12 chapters, every method name anchored to this repo's real data (819+ Methods, 23 categories, 15 skills), zero fabrication:
| # | Chapter | Focus |
|---|---|---|
| 引言 | Why this book | Why 3DGS is the key puzzle piece of Physical AI |
| CH 01 | NeRF → 3DGS: A paradigm leap | Explicit vs implicit, the three innovations, the alpha-compositing formula |
| CH 02 | The math & engineering core | Anisotropic Gaussians, differentiable rasterization, adaptive density control, CUDA |
| CH 03 | From scene to world | Large-scale, dynamic/4D, GS-SLAM, compression & deployment |
| CH 04 | Semantic Gaussians | CLIP/DINO feature distillation, open-vocabulary 3D segmentation |
| CH 05 | Editing · Generation · Asset-ization | Feed-forward reconstruction, SDS generation, animatable assets, PBR relighting |
| CH 06 | Embodied intelligence basics | VLA lineage (RT/π0/GR00T/ReconVLA), simulation, Sim2Real |
| CH 06 | 3DGS as robot spatial memory | GS-SLAM, map-as-renderer, three tiers of spatial memory |
| CH 08 | Object-level & articulated understanding | Part-level Gaussians, URDF bridging, the CAD·Mesh·3DGS triangle |
| CH 09 | Agent-driven digital twins | MCP rendering pipeline, gesture interaction, the perception-action loop |
| CH 10 | World models & the future | Six schools of world models, 3DGS×World Model, spatial foundation models, Physical AI |
| 后记 | Will 3DGS be eaten? | Why explicit representations will be compressed, not consumed |
Each chapter ends with hands-on exercises and links back to the repo's method tables, references/, and skills — so reading the book and doing the engineering are one seamless flow.
Highlights you won't find in a paper list:
- The six schools of world models (2026 taxonomy) and where 3DGS sits as the only representation that is simultaneously renderable, differentiable, and editable.
- How
GS-World,ManiGaussian, andOrbiSimturn 3DGS into a differentiable simulation engine. - A three-tier model of robot spatial memory (geometric → appearance → semantic) and where current GS-SLAM actually stands.
This book is the narrative layer over the repo's data layer. The repo gives you 819+ method names, abstracts, and 15 engineering skills — but not the through-line that connects them. The book supplies that through-line: it argues why 3DGS became the bridge between spatial intelligence and embodied intelligence, and walks every chapter back to concrete methods and skills you can use today. Read the book to understand the map; use the repo to ship the territory.
What's New (Aug 2026)
Latest update (Sep 4): v0.8.3 — Dynamic Scene Survey Integration: 23 New Methods. Knowledge base expanded from 801→819 verified methods. Added 23 arXiv-verified dynamic scene reconstruction methods from survey paper (连振晗 et al., J CAD & CG, Jan 2026), spanning 3 categories: deformation field (LoopGaussian, CoGS, CD-GS, PGED, GPS-Gaussian, MoDGS, MoDec-GS, SpectroMotion, BARD-GS, GauFRE, ReconDreamer++), sparse-control deformation (SP-GS, Video-3DGS, SplineGS), 4D Gaussian primitive (Real-time 4DGS, PVG, 4D-rotor GS), and per-frame inter-frame transfer (3DGStream, Dual-GS, STC-GS, IGS, GFlow, DynOMo). Dynamic & 4D category: 75→97. New references/dynamic-datasets.md (11 datasets) and expanded benchmark-data.md (MS-SSIM/VMAF/FID metrics + 4 performance comparison tables). Experiment planner skill updated with dynamic scene design guide. See changelog/2026-09-04.md.
Previous (Sep 2): v0.8.2 — Daily Update: 11 New Methods. Knowledge base expanded from 790→801 verified methods. New additions span 7 categories: BRF-GS (hyperspectral BRDF modeling with 3DGS), SMG (ECCV 2026, semantic motion graph for dynamic GS), VCAR (ACM MM 2026, training-free 3DGS segmentation), RealCAD (real-world image to CAD reconstruction), ObjectSplat (object-level mesh splatting), CapFrame (ECCV 2026, text-instructed viewpoint localization), Amortized Anchor Refinement (continuous-time 4D reconstruction), ATGS (SIGGRAPH 2026, anchored temporal GS for long volumetric video), CausalSplat (hierarchical causal reasoning in 3DGS), VoroTracing (623 FPS differentiable ray tracing), Lucida (Real-to-Sim composable scene modeling). All arXiv IDs verified, data CI passed. See changelog/2026-09-02.md.
Previous (Aug 23): v0.8.1 — Daily Update: 7 New Methods. Knowledge base expanded from 783→790 verified methods. New additions span 6 categories: LEGO (ECCV 2026, hierarchical language GS with LLM spatial reasoning), OutLangSplat (UAV outdoor open-vocabulary 3D language GS), ESVR (IEEE VIS 2026, 3D ellipsoid sparse volume rendering with 4 orders of magnitude compression), TRACE-GS (sparse-view 3DGS via privileged geometric conditioning), RORA (single-video-to-articulated-object pipeline with Unreal Engine deployment), OVOW (ECCV 2026, monocular video to instance-level 4D mesh for physics simulation), Super-Gaussian (interactive 3DGS scene editing with VR NLI visualization). All arXiv IDs verified, data CI passed. See changelog/2026-08-23.md.
Previous (Aug 7): v0.8.0 — Platform Upgrade (P0+P1+P2). Knowledge layer: single source of truth (data/methods.json, 783 methods, 23 categories) with data CI; 5 fabricated entries purged; 14 arXiv-verified frontier methods added. Capability layer: true-3DGS render loop (gsplat via HTTP-served PLY), server-authoritative scene persistence, real PLY/SPLAT export, 5 distinct prune strategies, grid-accelerated ray query, runtime arg validation, WS origin allowlist, 21 unit tests. Platform layer: Benchmark arena (bench/), skill orchestration contracts (skills/_contracts/), Router manifest loader (scripts/router_load.py). 13 core MCP tools (all real) + 13 experimental (gated by INCLUDE_EXPERIMENTAL=1). See changelog/2026-08-07.md.
Previous (Jul 26): v0.5.1 — Full Method Audit & 14 New Methods. Now 789+ Methods (775 verified unique baseline + 14 new). Full re-audit across 11 source files; all method counts unified to 789+. New additions: GrainGS (dynamic, 36.98 dB / 435.6 FPS / 4.67 MB), GLAM-SLAM (IROS 2026, outdoor decoupled SLAM), SubSplat (subpixel feed-forward), ATSplat (adaptive 3D tokens, 1136 FPS), 3D-GIMP (3DGS inpainting), LB-Edit (7× lower editing latency), FlexiAvatar (ECCV 2026, visible-body-only optimization), ZeroSplat (ECCV 2026, training-free segmentation), CaT-GS (CVPR 2026, 10× faster rendering), FF-ProCams (projector-camera inverse rendering), i3dgs (SIGGRAPH 2026, large-scale unordered), VIGS-SLAM (ECCV 2026, iPhone real-time), ECoNGS (IEEE VIS 2026, volume visualization), AniGS (scene-level animation via diffusion prior). +MoDE/MoE-GS c