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.

📖 Read the Book →

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, and OrbiSim turn 3DGS into a differentiable simulation engine.
• A three-tier model of robot spatial memory (geometric → appearance → semantic) and where current GS-SLAM actually stands.

Why we wrote it (and how it relates to this repo)

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 code link. Previous (Jul 24): v0.5.0 MCP Protocol Implementation. Previous (Jul 23): v0.4.3 ICML 2026 & Material/Provenance Wave — GaussTrace (ICML 2026), GADA (ICML 2026), InvSplat, MGM, DualPhys-GS, StereoGS. v0.4.4 added 3dgs-training-debugger skill (60+ runtime patterns).

Method	Venue	Category	One-Line Innovation
Proxy-GS	CVPR 2026 Oral	Acceleration	Lightweight proxy model for 2.5x speedup with no accuracy loss
Z-Order GS	CVPR 2026 Oral	Feed-Forward	Z-order Morton curve + sparse attention O(N²)→O(N log N)
3DReflecNet	CVPR 2026 Best Paper Candidate	Cross-Domain	120K+ objects, 48 material combos, 3 failure modes
Flux-GS	ECCV 2026	Acceleration	Flux-based Gaussian splatting for real-time rendering
AnchorSplat	ECCV 2026	Optimization	Anchor-driven splatting with efficient density control
ASSEMCAD	ECCV 2026	CAD	Assembly-aware CAD reconstruction from 3DGS
WildSplat	ECCV 2026	Robustness	In-the-wild scene reconstruction with transient object removal
NoDrift3R	ECCV 2026	SLAM	Drift-free dense 3D reconstruction via point map regression
Axis-Shared Rasterization Accelerator	ISCA 2026	Acceleration	Hardware accelerator with axis-shared tiled rasterization
Prune Wisely	—	Optimization	90% Gaussian pruning via DoG importance criterion
Provable Pruning via Coresets	—	Optimization	Coreset-based provable Gaussian pruning with bounded error
StreamLoD-GS	—	Streaming	LoD-based progressive streaming with view-dependent quality
CADDreamer	CVPR 2025 Highlight	CAD	Text/sketch → CAD B-rep generation
GaussTrace	ICML 2026	Security	3DGS provenance analysis via LLM reasoning for IP forensics
GADA	ICML 2026	Feed-Forward	Geometry-aware deformable aggregation, 2.13× faster FPS
InvSplat	arXiv 2026	Feed-Forward	Inverse feed-forward splatting with intrinsic PBR materials
MGM	arXiv 2026	Relighting	Large material Gaussian model for relightable 3D generation
DualPhys-GS	arXiv 2026	Robustness	Dual physics-guided 3DGS for underwater reconstruction
StereoGS	2026	Acceleration	Energy-efficient hardware stereoscopic GS rendering processor

^{Full changelog: changelog/}

Quick Start

Each skill is a standalone SKILL.md file — copy it to your Agent's skills directory.

3 commands to your first AI-powered 3DGS workflow:

git clone https://github.com/jaccen/Awesome-Gaussian-Skills.git

# Option 1: Claude Code
cp -r Awesome-Gaussian-Skills/skills/* .claude/

# Option 2: Cursor
cp -r Awesome-Gaussian-Skills/skills/* .cursor/rules/

# Option 3: One-Click Install
curl -sSL https://raw.githubusercontent.com/jaccen/Awesome-Gaussian-Skills/main/scripts/setup.sh | bash

Then ask your Agent: "Compare 3DGS and 2DGS rendering formulations"

Knowledge Base (819+ Methods, 23 Categories)

Group	Categories	Key Topics
Core Representations	Foundation, Antialiasing, Optimization, Surface/Rendering, Image Rep.	3DGS, 2DGS, Scaffold-GS, Mip-Splatting, GaussianImage
Efficiency & Scale	Compression, Acceleration, Large-Scale, Feed-Forward	Compact-3DGS, BlitzGS, HiGS, VEDAL, VG²GT
Understanding & Semantics	Language/Semantic, Generation, Autonomous Driving	LangSplat, DreamGaussian, StreetNVS
Dynamic & Spatial	Dynamic, HDR, SLAM, Sparse-View, Spatial Intelligence	DSD-GS, WebSpline, GGD-SLAM, Holi-Spatial, Spatial-TTT
Applications	Human/Avatar, Editing, Relighting, CAD, Cross-Domain, Simulation, Robotics, +14 more	AlbedoEdit, KDH-CAD, LEGS, TIDES, 3DEditSafe

Download full database: CSV | Full analysis: references/3dgs-methods-overview.md

Full Category Table (23 categories)

Core Representations

Category	Description	Methods
Foundation (40)	Core 3DGS representations and basic variants	3D Representation Survey, 3DGEER, 3DSGS
Optimization (76)	Training objectives, density control, convergence	AdaGScale, AdpSplit, ArtifactWorld
Surface & Rendering (50)	Surface extraction and rendering-formulation innovation	2D-SuGaR, 3DSS, AmbiSuR

Efficiency & Scale

Category	Description	Methods
Compression & Streaming (43)	Lightweight, mobile, and progressive streaming	CAGS, Clustered Codebook VQ, CodecSplat
Acceleration (10)	Training and inference speedup	3DGS\u00B3, Axis-Shared Rasterization Accelerator, DDF-GS
Large-Scale (20)	City-scale and distributed scene management	BlitzGS, CaT-GS, City-Level 3D Surface
Feed-Forward (67)	Generalizable single-pass reconstruction (incl. foundation models)	AdaptSplat, AnchorSplat, AnyCity

Understanding & Semantics

Category	Description	Methods
Language & Semantic (37)	Open-vocabulary 3D understanding and language fields	3D-GIMP, Consistent Scene Understanding in 3DGS, DGSG-Mind
Generation (27)	Text/condition-driven 3D/4D generation	AniGen, AnySurf, AssetGen
Autonomous Driving (33)	Driving scene reconstruction and simulation	3DGS Safety Evaluation for AD, Asset Harvester, CGGS

Dynamic & Spatial

Category	Description	Methods
Dynamic & 4D (97)	4D Gaussians, temporal deformation, physics-integrated dynamics	3DGS³, AniGS, ClipGStream
HDR & Relighting (27)	HDR capture, relightable and material-aware Gaussians	AlbedoEdit, Ambient-Robust IR, DiffAdapt4DSI
SLAM (40)	Simultaneous localization and mapping	2DGS-SLAM, Anchor3R, Anythingreality
Sparse-View (21)	Few-shot and sparse-view reconstruction	DropAnSH-GS, FrameTwin, GeoQuery
World Models & Spatial Intelligence (8)	3D spatial reasoning, world modeling	ABot-3DWorld 0, APEIRIA, FlashWorld

Applications & Cross-Domain

Category	Description	Methods
Human & Avatar (43)	Animatable human and avatar reconstruction	ArtMesh, CapTalk, COSY
Editing (47)	Interactive and text-guided scene editing	BEA-GS, Capacity-Controlled Stylization, DeSplat
CAD & Reverse Engineering (20)	CAD fitting, B-rep reconstruction, reverse engineering	3DCodeBench, ASSEMCAD, BRepCLIP
Cross-Domain (47)	Medical, underwater, remote sensing and other domains	3DTV, Aes3D, AsyncEvGS
Simulation (11)	Physics simulation and surrogate models	3DThinkVLA, AGILE, ArtiTwinSplat
Embodied AI & Robotics (30)	Grasping, manipulation, navigation, digital twins	3DGS Demo Synthesis (IL), ArtGS, Forecast-GS
Robustness (11)	In-the-wild and degradation-robust reconstruction	3DReflecNet, DelowlightSplat, DualPhys-GS
Security (13)	Watermarking, copyright, forgery detection	3DEditSafe, 4D-GSW, BitC-3DGS

15 AI-Powered Skills

#	Skill	What It Does	Example
1	3dgs-paper-reader	Read any 3DGS paper, extract structured insights	"帮我读一下 2401.01345"
2	3dgs-method-compare	Compare variants across 10+ dimensions	"对比 3DGS 和 2DGS 的渲染公式差异"
3	3dgs-code-reviewer	Catch 104 known 3DGS implementation bugs	"审查我的 CUDA 渲染 kernel"
4	3dgs-experiment-planner	Design experiments for CVPR/SIGGRAPH/TVCG	"帮我设计消融实验"
5	nerf-to-3dgs-migrator	Migrate NeRF methods to 3DGS step-by-step	"hash encoding 怎么迁移到 3DGS？"
6	cad-mesh-3dgs	Bridge CAD/Mesh/3DGS — 40+ conversion methods	"3DGS模型怎么提取高质量mesh？"
7	cg-paper-writing	Write papers for CVPR/SIGGRAPH/TVCG with adversarial review	"帮我写论文引言"
8	3dgs-visualizer	Publication-quality radar charts, timelines, heatmaps	"画一个3DGS方法对比雷达图"
9	3dgs-engineering-guide	Deploy 3DGS from research to production (10 industry tracks)	"怎么部署3DGS做自动驾驶仿真？"
10	patent-software-ip	Generate patent applications & software copyrights	"生成专利申请文件"
11	3dgs-spatial-agent	Agent-driven 3D scene reasoning, CAD extraction, editing	"从3DGS中提取椅子的CAD模型"
12	3dgs-mcp-renderer	MCP-controlled Three.js/3DGS rendering bridge	"从上方看这个场景"
13	3dgs-articulated-reasoner	Articulated object reasoning and digital twin	"打开抽屉"
14	3dgs-compression-deploy	Compress & deploy 3DGS (quantize, prune, VQ, stream, Web/Mobile)	"3DGS模型怎么压缩到10MB？"
15	3dgs-training-debugger	Diagnose training failures: OOM, NaN, divergence, artifacts (60+ runtime patterns)	"训练OOM了怎么办？"

Works with Claude Code, Cursor, Windsurf, and other AI Agent frameworks.

Visualization Samples

Generated by 3dgs-visualizer — see Test/ for full-resolution files.

Radar Chart	Metrics Bar Chart

Quality vs Speed	Metrics Heatmap

Research Innovation Highlights

Derived from systematic gap analysis across 819+ Methods. Target venues: TVCG / CGF / CAD / T-RO / IJCV / ACM TOG.

I-01. Part-Aware Alpha-Compositing for Articulated Objects

Problem: Standard alpha-compositing causes color bleeding at part boundaries of articulated objects. ULF-Loc (CVPR 2026) exposed this feature bias, but no rendering-formulation-level fix exists.

Approach: Extend alpha-compositing with part-aware opacity modulation: C(θ) = Σ Tᵢ · αᵢ · ω_{p(i)}(θ) · cᵢ(θ), where ω penalizes penetration and joint violations, making inter-part penetration regions automatically transparent.

Path: 1) Build on gsplat rasterizer. 2) Add FK layer for articulated objects (URDF). 3) Compute penetration/joint violation via SDF. 4) Train on Articulate-100.

Target: SIGGRAPH / ACM TOG / TVCG

I-02. Geometry-Consistent Flow World Model for Manipulation

Problem: Flow-based world models (RoboFlow4D) predict dense 3D flows but lack geometric consistency — predicted flows can violate object rigidity and physical constraints.

Approach: Couple 3D flow prediction with scene graph constraints: rigidity loss for static objects, articulation loss for joints, support-relation constraints for stacking.

Path: 1) Extend RoboFlow4D. 2) Scene graph parser via OpenMask3D. 3) Geometric regularizer. 4) Train on LIBERO + RoboCasa.

Target: IJCV / T-RO / RSS

I-03. Multi-Scale Occupancy-Gaussian Bidirectional Bridge for Driving

Problem: Occupancy (SparseWorld, DOV) is the driving world model standard; 3DGS provides superior rendering. No differentiable bridge exists between them.

Approach: Bidirectional conversion: Occ→3DGS (learned position+scale predictor from occupancy+semantics) and 3DGS→Occ (differentiable sparse convolution pooling). Joint backbone for unified prediction+rendering.

Path: 1) Backbone: SparseWorld-TC. 2) Occ→3DGS module. 3) 3DGS→Occ module. 4) Training: nuScenes, Waymo.

Target: TVCG / T-ITS / CVPR

6 more innovation highlights (I-04 to I-10)

• I-04. Solid Geometry Neural-Symbolic Reasoning: VLM + Z3/SMT formal verifier in iterative refinement loop. Target: Pattern Recognition / AAAI.
• I-05. Embodied Spatial Memory: Hippocampus-inspired 3DGS scene graph + Perceiver compressor + importance-weighted forgetting. Target: T-RO / IJCV.
• I-06. Differentiable Physics Engine: SDF-based contact + differentiable KKT contact solver + Coulomb friction for manipulation. Target: ACM TOG / SIGGRAPH.
• I-06. Tactile-Visual Spatial Fusion: GelSight → contact geometry maps → 3D scene projection → cross-attention fusion. Target: T-RO / ICRA.
• I-08. Panoramic Spatial World Model: Spherical visual panorama + BEV semantic + affordance + spatial relation graph for "imagine then navigate". Target: ECCV / CVPR.
• I-09. Code-as-Spatial-Vocabulary: VLM generates Three.js code → render → extract spatial annotations → fine-tune VLM. Target: CVPR / NeurIPS.
• I-10. Hyperbolic Cross-Modal Distillation: Poincare ball distillation for image→point-cloud hierarchical feature transfer. Target: T-MM / T-IP.

Roadmap

• v0.1 — Initial release with 6 core skills (Apr 2026)
• v0.2 — 3dgs-visualizer + Text2Word demo (May 2026)
• v0.3 — Knowledge base 665->789+ Methods, 25 Categories, 101+ bug patterns, 12 skills (Jun 2026)
• v0.3.6 — Spatial intelligence wave: 680->639+ methods, +10 new methods (FastGS, Holi-Spatial, Spatial-TTT, etc.), Dimension 11, Anthropic standard alignment (Jun 25, 2026)
• v0.3.6 — CVPR 2026 representative papers: 690->639+ methods, +23 verified new methods, all 13 skills updated (Jun 28, 2026)
• v0.4.0 — Router Architecture