Awesome 3D Generation [](https://github.com/sindresorhus/awesome)
September 6, 2026 Β· View on GitHub
π― A curated list of papers on 3D generation with visual previews - see research at a glance.
π Papers are organized by different 3D representations: Mesh, SDF (Signed Distance Function), Point Cloud, NeRF, and more.
π We also include papers that, while not strictly about generation, demonstrate valuable techniques and insights for 3D generation research.
π You can also check our Project Homepage.
π₯π₯π₯ Also check out our awesome list about Neural CAD.
π Topics
Articulated 3D β’ Mesh β’ Implicit Shape Representations β’ Point Cloud β’ NeRF β’ 3D Gaussian Splatting β’ CAD β’ Voxel β’ Part-based 3D β’ 3D Editing β’ Automatic Rigging β’ Others β’ Industry Technical Reports
Articulated 3D
| Preview | Title | Publication | Links |
|---|---|---|---|
![]() | Instruct-Particulate: Scaling Feed-Forward 3D Object Articulation with Kinematic Control | arXiv 2026 | Paper Project |
![]() | Articraft: An Agentic System for Scalable Articulated 3D Asset Generation | arXiv 2026 | Paper Project |
![]() | Particulate: Feed-Forward 3D Object Articulation | CVPR 2026 | Paper Project |
![]() | PhysX-Anything: Simulation-Ready Physical 3D Assets from Single Image | CVPR 2026 | Paper Project Code |
![]() | URDF-Anything: Constructing Articulated Objects with 3D Multimodal Language Model | NeurIPS 2025 | Paper Project |
![]() | DreamArt: Generating Interactable Articulated Objects from a Single Image | arXiv 2025 | Paper Project |
![]() | MeshArt: Generating Articulated Meshes with Structure-guided Transformers | CVPR 2025 | Paper Code |
![]() | ArtFormer: Controllable Generation of Diverse 3D Articulated Objects | CVPR 2025 | Paper Code |
![]() | SINGAPO: Single Image Controlled Generation of Articulated Parts in Objects | ICLR 2025 | Paper Project Code |
![]() | CAGE: Controllable Articulation GEneration | CVPR 2024 | Paper Project Code |
![]() | NAP: Neural 3D Articulated Object Prior | NeurIPS 2023 | Paper Project Code |
Mesh
| Preview | Title | Publication | Links |
|---|---|---|---|
![]() | Meshy T2: Fast Native Mesh Generation with Flow Matching | arXiv 2026 | Paper Code |
![]() | Nexus: Native Mesh Generation with Diffusion | ACM TOG 2026 | Paper |
![]() | LATO.2: Factorized 3D Mesh Generation with Vertex and Topology Flow | arXiv 2026 | Paper Code |
![]() | Mesh BDF: Barycentric Dominance Field for 3D Native Mesh Generation | arXiv 2026 | Paper Project Code |
![]() | PolyFlow: Continuous Topology Embedding Flow Matching for Artist-style Mesh Generation | arXiv 2026 | Paper |
![]() | MeshFlow: Mesh Generation with Equivariant Flow Matching | SIGGRAPH 2026 | Paper Project Code |
![]() | LATO: 3D Mesh Flow Matching with Structured TOpology Preserving LAtents | ICML 2026 | Paper Project Code |
![]() | AssetFormer: Modular 3D Assets Generation with Autoregressive Transformer | ICLR 2026 | Paper |
![]() | MeshMosaic: Scaling Artist Mesh Generation via Local-to-Global Assembly | arXiv 2025 | Paper Project Code |
![]() | MeshCraft: Exploring Efficient and Controllable Mesh Generation with Flow-based DiTs | arXiv 2025 | Paper |
![]() | QuadGPT: Native Quadrilateral Mesh Generation with Autoregressive Models | arXiv 2025 | Paper |
![]() | ARMesh: Autoregressive Mesh Generation via Next-Level-of-Detail Prediction | arXiv 2025 | Paper Project |
![]() | MeshCoder: LLM-Powered Structured Mesh Code Generation from Point Clouds | arXiv 2025 | Paper Project Code |
![]() | VertexRegen: Mesh Generation with Continuous Level of Detail | arXiv 2025 | Paper Project |
![]() | FastMesh: Efficient Artistic Mesh Generation via Component Decoupling | arXiv 2025 | Paper |
![]() | LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models | arXiv 2024 | Paper Code Demo |
![]() | FreeMesh: Boosting Mesh Generation with Coordinates Merging | ICML 2025 | Paper |
![]() | Mesh-RFT: Enhancing Mesh Generation via Fine-grained Reinforcement Fine-Tuning | arXiv 2025 | Paper |
![]() | Scaling mesh generation via compressive tokenization | CVPR 2025 | Paper Project Code |
![]() | iFlame: Interleaving Full and Linear Attention for Efficient Mesh Generation | arXiv 2025 | Paper Code |
![]() | Mesh Silksong: Auto-Regressive Mesh Generation as Weaving Silk | arXiv 2025 | Paper |
![]() | MeshPad: Interactive Sketch-Conditioned Artist-Designed Mesh Generation and Editing | arXiv 2025 | Paper Project |
![]() | DeepMesh: Auto-Regressive Artist-mesh Creation with Reinforcement Learning | ICCV 2025 | Paper Project Code |
![]() | EdgeRunner: Auto-regressive Auto-encoder for Artistic Mesh Generation | ICLR 2025 | Paper Code |
![]() | MeshArt: Generating Articulated Meshes with Structure-guided Transformers | CVPR 2025 | Paper Code |
![]() | TreeMeshGPT: Topology-Aware Mesh Generation with Tree-Structured Graph Priors | CVPR 2025 | Paper |
![]() | Meshtron: High-Fidelity, Artist-Like 3D Mesh Generation at Scale | arXiv 2024 | Paper Project |
![]() | MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh Tokenization | ICCV 2025 | Paper Project Code |
![]() | MeshXL: Neural Coordinate Field for Generative 3D Foundation Models | NeurIPS 2024 | Paper Code |
![]() | SpaceMesh: A Continuous Representation for Learning Manifold Surface Meshes | SIGGRAPH Asia 2024 | Paper Project |
![]() | PivotMesh: Generic 3D Mesh Generation via Pivot Vertices Guidance | ICLR 2025 | Paper Project Code |
![]() | MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers | ICLR 2025 | Paper Project Code |
![]() | MeshGPT: Generating Triangle Meshes with Decoder-Only Transformers | CVPR 2024 | Paper Code |
![]() | PolyDiff: Generating 3D Polygonal Meshes with Diffusion Models | arXiv 2023 | Paper |
![]() | PolyGen: An Autoregressive Generative Model of 3D Meshes | ICML 2020 | Paper Code |
Implicit Shape Representations (SDF and Occupancy Fields, etc.)
| Preview | Title | Publication | Links |
|---|---|---|---|
![]() | ActionMesh: Animated 3D Mesh Generation with Temporal 3D Diffusion | arXiv 2026 | Paper Project Code |
![]() | UltraShape 1.0: High-Fidelity 3D Shape Generation via Scalable Geometric Refinement | arXiv 2025 | Paper Project Code |
![]() | LATTICE: Democratize High-Fidelity 3D Generation at Scale | arXiv 2025 | Paper Project Code |
![]() | UniLat3D: Geometry-Appearance Unified Latents for Single-Stage 3D Generation | arXiv 2025 | Paper Project Code |
![]() | HierOctFusion: Multi-scale Octree-based 3D Shape Generation via Part-Whole-Hierarchy Message Passing | arXiv 2024 | Paper |
![]() | Ultra3D: Efficient and High-Fidelity 3D Generation with Part Attention | arXiv 2025 | Paper Project |
![]() | Sparc3D: Sparse Representation and Construction for High-Resolution 3D Shapes Modeling | arXiv 2025 | Paper |
![]() | OctGPT: Octree-based Multiscale Autoregressive Models for 3D Shape Generation | SIGGRAPH 2025 | Paper Code |
![]() | SparseFlex: High-Resolution and Arbitrary-Topology 3D Shape Modeling (TripoSF) | arXiv 2025 | Paper Code |
![]() | TRELLIS: Structured 3D Latents for Scalable and Versatile 3D Generation | CVPR 2025 | Paper Code |
![]() | SplatSDF: Boosting Neural Implicit SDF via Gaussian Splatting Fusion | arXiv 2024 | Paper |
![]() | LaGeM: A Large Geometry Model for 3D Representation Learning and Diffusion | ICLR 2025 | Paper Code Project |
![]() | OctFusion: Octree-based Diffusion Models for 3D Shape Generation | SGP 2025 | Paper Code |
![]() | MeshFormer: High-Quality Mesh Generation with 3D-Guided Reconstruction Model | arXiv 2024 | Paper |
![]() | SurroundSDF: Implicit 3D Scene Understanding Based on Signed Distance Field | CVPR 2024 | Paper |
![]() | CraftsMan: High-fidelity Mesh Generation with 3D Native Generation and Interactive Geometry Refiner | arXiv 2024 | Paper Code |
![]() | GSDF: 3DGS Meets SDF for Improved Neural Rendering and Reconstruction | NeurIPS 2024 | Paper |
![]() | HSDF: Hybrid Sign and Distance Field for Neural Representation of Surfaces With Arbitrary Topologies | IEEE 2024 | Paper |
![]() | GEM3D: GEnerative Medial Abstractions for 3D Shape Synthesis | SIGGRAPH 2024 | Paper Code Project |
![]() | Mosaic-SDF for 3D Generative Models | arXiv 2024 | Paper |
![]() | XCube: Large-Scale 3D Generative Modeling using Sparse Voxel Hierarchies | CVPR 2024 | Paper Code |
![]() | Constructive Solid Geometry on Neural Signed Distance Fields | ACM SIGGRAPH Asia 2023 | Paper Project |
![]() | Diffusion-SDF: Conditional Generative Modeling of Signed Distance Functions | ICCV 2023 | Paper Project |
![]() | SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation | CVPR 2023 | Paper Code |
![]() | Locally Attentional SDF Diffusion for Controllable 3D Shape Generation | ACM TOG 2023 | Paper |
![]() | MeshDiffusion: Score-based Generative 3D Mesh Modeling | ICLR 2023 | Paper Code |
![]() | 3DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Models | ACM TOG 2023 | Paper Code |
![]() | SDF-Diffusion: Text-to-Shape via Voxelized Diffusion | CVPR 2023 | Paper |
![]() | Neural Wavelet-domain Diffusion for 3D Shape Generation, Inversion, and Manipulation | SIGGRAPH Asia 2022 ACM TOG | Paper Code |
![]() | SDF-StyleGAN: Implicit SDF-Based StyleGAN for 3D Shape Generation | SGP 2022 | Paper Code |
![]() | 3DILG: Irregular Latent Grids for 3D Generative Modeling | NeurIPS 2022 | Paper Code Project |
![]() | AutoSDF: Shape Priors for 3D Completion, Reconstruction and Generation | CVPR 2022 | Paper |
![]() | NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction | NeurIPS 2021 | Paper Code |
![]() | Neural Unsigned Distance Fields for Implicit Function Learning | NeurIPS 2020 | Paper |
![]() | SIREN: Implicit Neural Representations with Periodic Activation Functions | NeurIPS 2020 | Paper Code |
![]() | Convolutional Occupancy Networks | ECCV 2020 | Paper Code |
![]() | DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation | CVPR 2019 | Paper Code |
![]() | IM-Net: Learning Implicit Fields for Generative Shape Modeling | CVPR 2019 | Paper Code |
Point Cloud
| Preview | Title | Publication | Links |
|---|---|---|---|
![]() | TopoDiT-3D: Topology-Aware Diffusion Transformer with Bottleneck Structure for 3D Point Cloud Generation | arXiv 2025 | Paper |
![]() | 3D Point Cloud Generation via Autoregressive Up-sampling | arXiv 2025 | Paper |
![]() | EAGLE: Contextual Point Cloud Generation via Adaptive Continuous Normalizing Flow with Self-Attention | arXiv 2025 | Paper |
![]() | Not-So-Optimal Transport Flows for 3D Point Cloud Generation | arXiv 2025 | Paper |
![]() | RGB2Point: 3D Point Cloud Generation from Single RGB Images | arXiv 2024 | Paper |
![]() | Fast Training of Diffusion Transformer with Extreme Masking for 3D Point Clouds Generation | ECCV 2024 | Paper |
![]() | Context-Aware Indoor Point Cloud Object Generation through User Instructions | ACM Multimedia 2024 | Paper |
![]() | Learning to Generate 3D Shapes with Generative Cellular Automata | ICLR 2021 | Paper |
![]() | 3D Shape Generation and Completion through Point-Voxel Diffusion | ICCV 2021 | Paper Code |
NeRF
| Preview | Title | Publication | Links |
|---|---|---|---|
![]() | One-2-3-45++: Fast Single Image to 3D Objects with Consistent Multi-View Generation and 3D Diffusion | CVPR 2024 | Paper Project |
![]() | ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation | NeurIPS 2023 | Paper Code Project |
![]() | One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimization | NeurIPS 2023 | Paper Code Project |
![]() | Zero-1-to-3: Zero-shot One Image to 3D Object | ICCV 2023 | Paper Code Project |
![]() | Magic3D: High-Resolution Text-to-3D Content Creation | CVPR 2023 | Paper Project |
![]() | DreamFusion: Text-to-3D using 2D Diffusion | arXiv 2022 | Paper Project |
![]() | Efficient Geometry-aware 3D Generative Adversarial Networks | CVPR 2022 | Paper Code Project |
3D Gaussian Splatting
| Preview | Title | Publication | Links |
|---|---|---|---|
![]() | VRSplat: Fast and Robust Gaussian Splatting for Virtual Reality | arXiv 2025 | Paper |
![]() | Gaussian Splatting with Discretized SDF for Relightable Assets | arXiv 2025 | Paper |
![]() | Enhancing 3D Gaussian Splatting Compression via Spatial Condition-based Prediction | arXiv 2025 | Paper |
![]() | 3D Gaussian Splatting as a New Era: A Survey | IEEE TVCG 2024 | Paper |
![]() | WildGaussians: 3D Gaussian Splatting In the Wild | NeurIPS 2024 | Paper |
![]() | Spec-Gaussian: Anisotropic View-Dependent Appearance for 3D Gaussian Splatting | NeurIPS 2024 | Paper |
![]() | ODGS: 3D Scene Reconstruction from Omnidirectional Images with 3D Gaussian Splattings | NeurIPS 2024 | Paper Code |
![]() | DOGS: Distributed-Oriented Gaussian Splatting for Large-Scale 3D Reconstruction | NeurIPS 2024 | Paper Code |
![]() | FreeSplat: Generalizable 3D Gaussian Splatting for Free-View Synthesis | NeurIPS 2024 | Paper Code |
![]() | 3D Gaussian Splatting as Markov Chain Monte Carlo | NeurIPS 2024 (Spotlight) | Paper |
![]() | 3iGS: Factorised Tensorial Illumination for 3D Gaussian Splatting | ECCV 2024 | Paper |
![]() | HeadStudio: Text to Animatable Head Avatars with 3D Gaussian Splatting | ECCV 2024 | Paper |
![]() | Gaussian Grouping: Segment and Edit Anything in 3D Scenes | ECCV 2024 | Paper Code |
![]() | 2D Gaussian Splatting for Geometrically Accurate Radiance Fields | SIGGRAPH 2024 | Paper Code |
![]() | Recent Advances in 3D Gaussian Splatting | arXiv 2024 | Paper |
![]() | COLMAP-Free 3D Gaussian Splatting | CVPR 2024 | Paper |
![]() | Gaussian Splatting SLAM | CVPR 2024 (Best Demo) | Paper |
![]() | Mip-Splatting: Alias-free 3D Gaussian Splatting | CVPR 2024 (Best Student Paper) | Paper Code |
![]() | DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation | ICLR 2024 (Oral) | Paper Code |
![]() | 3D Gaussian Splatting for Real-Time Radiance Field Rendering | SIGGRAPH 2023 | Paper Code |
![]() | A Survey on 3D Gaussian Splatting | arXiv 2024 | Paper |
![]() | SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering | CVPR 2024 | Paper Code |
CAD
| Preview | Title | Publication | Links |
|---|---|---|---|
![]() | ReCAD: Reinforcement Learning Enhanced Parametric CAD Model Generation with Vision-Language Models | arXiv 2025 | Paper |
![]() | BrepGPT: Autoregressive B-rep Generation with Voronoi Half-Patch | SIGGRAPH Asia 2025 | Paper Code |
![]() | AutoBrep: Autoregressive B-Rep Generation with Unified Topology and Geometry | SIGGRAPH Asia 2025 | Paper Code |
![]() | GeoCAD: Local Geometry-Controllable CAD Generation | NeurIPS 2025 | Paper Code |
![]() | CAD-Coder: Text-to-CAD Generation with Chain-of-Thought and Geometric Reward | arXiv 2025 | Paper |
![]() | Stitch-A-Shape: Bottom-up Learning for B-Rep Generation | SIGGRAPH 2025 | Paper |
![]() | BrepDiff: Single-stage B-rep Diffusion Model | SIGGRAPH 2025 | Paper Project |
![]() | HoLa: B-Rep Generation using a Holistic Latent Representation | SIGGRAPH 2025 | Paper Project |
![]() | CLR-Wire: Towards Continuous Latent Representations for 3D Curve Wireframe Generation | SIGGRAPH 2025 | Paper Code |
![]() | DTGBrepGen: A Novel B-rep Generative Model through Decoupling Topology and Geometry | CVPR 2025 | Paper Code Project |
![]() | CADCrafter: Generating Computer-Aided Design Models from Unconstrained Images | CVPR 2025 | Paper |
![]() | CADDreamer: CAD object Generation from Single-view Images | CVPR 2025 | Paper Project |
![]() | CAD-GPT: Synthesising CAD Construction Sequence with Spatial Reasoning-Enhanced Multimodal LLMs | arXiv 2025 | Paper Project |
![]() | Text-to-CAD Generation Through Infusing Visual Feedback in Large Language Models | arXiv 2025 | Paper |
![]() | Revisiting CAD Model Generation by Learning Raster Sketch | AAAI 2025 | Paper Dataset |
![]() | FlexCAD: Unified and Versatile Controllable CAD Generation with Fine-tuned Large Language Models | ICLR 2025 | Paper Code |
![]() | Generating CAD Code with Vision-Language Models for 3D Designs | ICLR 2025 | Paper Code |
![]() | Donβt Mesh with Me: Generating Constructive Solid Geometry Instead of Meshes by Fine-Tuning a Code-Generation LLM | arXiv 2024 | Paper |
![]() | CAD-MLLM: Unifying Multimodality-Conditioned CAD Generation With MLLM | arXiv 2024 | Paper Project |
![]() | Text2CAD: Text to 3D CAD Generation via Technical Drawings | NeurIPS 2024 | Paper Code Project |
![]() | CadVLM: Bridging Language and Vision in the Generation of Parametric CAD Sketches | ECCV 2024 | Paper |
![]() | BrepGen: A B-rep Generative Diffusion Model with Structured Latent Geometry | SIGGRAPH 2024 | Paper Code |
![]() | Learn to Create Simple LEGO Micro Buildings | SIGGRAPH Asia 2024 | Paper Code |
![]() | Generating 3D House Wireframes with Semantics | ECCV 2024 | Paper Project |
![]() | SolidGen: An Autoregressive Model for Direct B-rep Synthesis | ICLR 2024 | Paper |
![]() | Brep2Seq: A Dataset and Hierarchical Deep Learning Network for Reconstruction and Generation of Computer-Aided Design Models | JCDE 2024 | Paper Code |
![]() | VQ-CAD: Computer-Aided Design model generation with vector quantized diffusion | CAGD 2024 | Paper |
![]() | PartNeRF: Generating Part-Aware Editable 3D Shapes without 3D Supervision | CVPR 2023 | Paper Code Project |
![]() | Hierarchical Neural Coding for Controllable CAD Model Generation | ICML 2023 | Paper Code Project |
![]() | SkexGen: Autoregressive Generation of CAD Construction Sequences with Disentangled Codebooks | ICML 2022 | Paper Code Project |
![]() | Free2CAD: Parsing Freehand Drawings into CAD Commands | SIGGRAPH 2022 | Code Project |
![]() | DeepCAD: A Deep Generative Network for Computer-Aided Design Models | ICCV 2021 | Paper Code Project |
![]() | Roof-GAN: Learning to Generate Roof Geometry and Relations for Residential Houses | CVPR 2021 | Paper Code |
![]() | Computer-aided design as language | NeurIPS 2021 | Paper |
![]() | SDM-NET: Deep Generative Network for Structured Deformable Mesh | TOG 2019 | Paper Code |
![]() | StructureNet: Hierarchical Graph Networks for 3D Shape Generation | Siggraph Asia 2019 | Paper Code Project |
![]() | AtlasNet: A Papier-MΓ’chΓ© Approach to Learning 3D Surface Generation | CVPR 2018 | Paper Code Project |
Voxel
| Preview | Title | Publication | Links |
|---|---|---|---|
![]() | 3D molecule generation by denoising voxel grids | NeurIPS 2023 | Paper |
![]() | AutoSDF: Shape Priors for 3D Completion, Reconstruction and Generation | CVPR 2022 | Paper Code Project |
![]() | Octree Transformer: Autoregressive 3D Shape Generation on Hierarchically Structured Sequences | arXiv 2021 | Paper |
![]() | Generative VoxelNet: Learning Energy-Based Models for 3D Shape Synthesis and Analysis | TPAMI 2020 | Paper Code Project |
![]() | Learning Part Generation and Assembly for Structure-Aware Shape Synthesis | AAAI 2020 | Paper |
![]() | PQ-NET: A Generative Part Seq2Seq Network for 3D Shapes | CVPR 2020 | Paper Code |
![]() | Generalized Autoencoder for Volumetric Shape Generation | CVPRW 2020 | Paper Code |
![]() | SAGNet: Structure-aware Generative Network for 3D-Shape Modeling | SIGGRAPH 2019 | Paper Code Project |
![]() | Generative and Discriminative Voxel Modeling with Convolutional Neural Networks | arXiv 2016 | Paper Code |
![]() | Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling | NeurIPS 2016 | Paper Code Project |
Part-based 3D
| Preview | Title | Publication | Links |
|---|---|---|---|
![]() | PartNeXt: A Next-Generation Dataset for Fine-Grained and Hierarchical 3D Part Understanding | arXiv 2025 | Paper |
![]() | FullPart: Generating each 3D Part at Full Resolution | arXiv 2025 | Paper |
![]() | PartSAM: A Scalable Promptable Part Segmentation Model Trained on Native 3D Data | arXiv 2025 | Paper |
![]() | BANG: Dividing 3D Assets via Generative Exploded Dynamics | arXiv 2025 | Paper |
![]() | AutoPartGen: Autoregressive 3D Part Generation and Discovery | NeurIPS 2025 | Paper |
![]() | From One to More: Contextual Part Latents for 3D Generation | ICCV 2025 | Paper Project |
![]() | Assembler: Scalable 3D Part Assembly via Anchor Point Diffusion | arXiv 2025 | Paper |
![]() | Efficient Part-level 3D Object Generation via Dual Volume Packing | arXiv 2025 | Paper |
![]() | MeshArt: Generating Articulated Meshes with Structure-guided Transformers | CVPR 2025 | Paper Code |
![]() | PrimitiveAnything: Human-Crafted 3D Primitive Assembly Generation with Auto-Regressive Transformer | SIGGRAPH 2025 | Paper Code |
![]() | OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesion | arXiv 2025 | Paper |
![]() | PartCrafter: Structured 3D Mesh Generation via Compositional Latent Diffusion Transformers | arXiv 2025 | Paper |
![]() | HoloPart: Generative 3D Part Amodal Segmentation | arXiv 2025 | Paper Code |
![]() | PartField: Learning 3D Feature Fields for Part Segmentation and Beyond | ICCV 2025 | Paper Project Code |
![]() | SPAFormer: Sequential 3D Part Assembly with Transformers | 3DV 2025 | Paper Code |
![]() | PASTA: Controllable Part-Aware Shape Generation with Autoregressive Transformers | arXiv 2024 | Paper |
![]() | SAMPart3D: Segment Any Part in 3D Objects | arXiv 2024 | Paper Project |
![]() | PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models | CVPR 2025 | Paper Project |
![]() | Part123: Part-aware 3D Reconstruction from a Single-view Image | SIGGRAPH 2024 | Paper Project |
![]() | Part-aware Shape Generation with Latent 3D Diffusion of Neural Voxel Fields | IEEE TVCG | Paper |
![]() | DAE-Net: Deforming Auto-Encoder for fine-grained shape co-segmentation | SIGGRAPH 2024 | Paper Code |
![]() | StructureNet: Hierarchical Graph Networks for 3D Shape Generation | SIGGRAPH Asia 2019 | Paper Code |
![]() | PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understanding | CVPR 2019 | Paper Dataset |
![]() | Generative 3D Part Assembly via Dynamic Graph Learning | NeurIPS 2020 | Paper Code |
![]() | ComplementMe: Weakly-Supervised Component Suggestions for 3D Modeling | SIGGRAPH Asia 2017 | Paper |
![]() | BSP-Net: Generating Compact Meshes via Binary Space Partitioning | CVPR 2020 | Paper Code |
![]() | GRASS: Generative Recursive Autoencoders for Shape Structures | SIGGRAPH 2017 | Paper |
![]() | Learning Part Generation and Assembly for Structure-Aware Shape Synthesis | AAAI 2020 | Paper |
![]() | Learning 3D Part Assembly from a Single Image | ECCV 2020 | Paper |
![]() | CompoNet: Learning to Generate the Unseen by Part Synthesis and Composition | ICCV 2019 | Paper |
![]() | ShapeAssembly: Learning to Generate Programs for 3D Shape Structure Synthesis | SIGGRAPH Asia 2020 | Paper Code |
![]() | Part-based 3D Object Reconstruction from a Single RGB Image | arXiv 2021 | Paper |
![]() | PartSLIP: Low-shot Part Segmentation for 3D Point Clouds via Pretrained Image-Language Models | CVPR 2023 | Paper Code |
![]() | Unsupervised Learning of Shape Programs with Repeatable Implicit Parts | NeurIPS 2022 | Paper Project |
![]() | SPAGHETTI: Editing Implicit Shapes Through Part Aware Generation | ACM TOG 2022 | Paper Code Project |
![]() | BAE-NET: Branched Autoencoder for Shape Co-Segmentation | ICCV 2019 | Paper Code |
3D Editing
| Preview | Title | Publication | Links |
|---|---|---|---|
![]() | Fuse3D: Generating 3D Assets Controlled by Multi-Image Fusion | SIGGRAPH Asia 2025 | Paper Project Code |
![]() | 3DGS-Drag: Dragging Gaussians for Intuitive Point-Based 3D Editing | ICLR 2025 | Paper |
![]() | Native 3D Editing with Full Attention | arXiv 2025 | Paper |
![]() | 3D-LATTE: Latent Space 3D Editing from Textual Instructions | arXiv 2025 | Paper Project |
![]() | Drag Your Gaussian: Effective Drag-Based Editing with Score Distillation for 3D Gaussian Splatting | SIGGRAPH 2025 | Paper Project Code |
![]() | Perturb-and-Revise: Flexible 3D Editing with Generative Trajectories | CVPR 2025 | Paper Project |
![]() | Instant3dit: Multiview Inpainting for Fast Editing of 3D Objects | CVPR 2025 | Paper Project Code |
![]() | ShapeFusion: A 3D Diffusion Model for Localized Shape Editing | ECCV 2024 | Paper Project |
![]() | GaussCtrl: Multi-View Consistent Text-Driven 3D Gaussian Splatting Editing | ECCV 2024 | Paper Project Code |
![]() | Gaussian Grouping: Segment and Edit Anything in 3D Scenes | ECCV 2024 | Paper Code |
![]() | GaussianEditor: Editing 3D Gaussians Delicately with Text Instructions | CVPR 2024 | Paper Project |
![]() | Instruct-NeRF2NeRF: Editing 3D Scenes with Instructions | ICCV 2023 | Paper Project Code |
Automatic Rigging
| Preview | Title | Publication | Links |
|---|---|---|---|
![]() | Auto-Connect: Connectivity-Preserving RigFormer with Direct Preference Optimization | arXiv 2025 | Paper Project |
![]() | One Model to Rig Them All: Diverse Skeleton Rigging with UniRig | SIGGRAPH 2025 | Paper Project Code |
![]() | RigAnything: Template-Free Autoregressive Rigging for Diverse 3D Assets | SIGGRAPH 2025 | Paper Project Code |
![]() | MagicArticulate: Make Your 3D Models Articulation-Ready | CVPR 2025 | Paper Project Code |
![]() | Make-It-Animatable: An Efficient Framework for Authoring Animation-Ready 3D Characters | CVPR 2025 | Paper Project Code |
![]() | HumanRig: Learning Automatic Rigging for Humanoid Character in a Large Scale Dataset | arXiv 2024 | Paper |
![]() | RigNet: Neural Rigging for Articulated Characters | SIGGRAPH 2020 | Paper Project Code |
![]() | TARig: Adaptive Template-Aware Neural Rigging for Humanoid Characters | Computers & Graphics 2023 | Paper |
![]() | Predicting Animation Skeletons for 3D Articulated Models via Volumetric Nets | 3DV 2019 | Paper Project Code |
![]() | Automatic Rigging and Animation of 3D Characters | SIGGRAPH 2007 | Paper Project Code |
Others (Not yet classified)
| Preview | Title | Publication | Links |
|---|---|---|---|
![]() | WorldGrow: Generating Infinite 3D World | arXiv 2025 | Paper Project Code |
![]() | Generative Human Geometry Distribution | Arxiv 2025 | Paper |
![]() | Geometry Distributions | ICCV 2025 | Paper |
![]() | Functional Diffusion | CVPR 2024 | Paper Code Project |
![]() | 3DTopia-XL: Scaling High-quality 3D Asset Generation via Primitive Diffusion | Arxiv 2024 | Paper |
![]() | Geometry Image Diffusion: Fast and Data-Efficient Text-to-3D with Image-Based Surface Representation | Arxiv 2024 | Paper |
| An Object is Worth 64Γ64 Pixels: Generating 3D Object via Image Diffusion | Arxiv 2024 | Paper | |
![]() | X-Ray: A Sequential 3D Representation for Generation | Arxiv 2024 | Paper |
![]() | MeshCNN: A Network with an Edge | SIGGRAPH 2019 | Paper Code |
![]() | Neural Marching Cubes | SIGGRAPH Asia 2021 | Paper Code |
![]() | As-Plausible-As-Possible: Plausibility-Aware Mesh Deformation Using 2D Diffusion Priors | CVPR 2024 | Project |
![]() | GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images | NeurIPS 2022 | Paper Code |
![]() | Single Mesh Diffusion Models with Field Latents for Texture Generation | arXiv 2023 | Paper |
Industry Technical Reports
| Preview | Title | Publication | Links |
|---|---|---|---|
![]() | [Tencent] Hunyuan3D 1.0: A Unified Framework for Text-to-3D and Image-to-3D Generation | 2024 | Paper Code Demo |
![]() | [Tencent] Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation | 2025 | Paper Code Website |
![]() | [Tencent] Hunyuan3D 2.1: From Images to High-Fidelity 3D Assets with Production-Ready PBR Material | 2025 | Paper Code |
![]() | [Tencent] Hunyuan3D 2.5: Towards High-Fidelity 3D Assets Generation with Ultimate Details | 2025 | Paper Code |
![]() | [Tencent] Hunyuan3D-Omni: A Unified Framework for Controllable Generation of 3D Assets | 2025 | Paper Code |
![]() | [ByteDance] Seed3D 1.0: Simulation-Ready 3D Asset Generation from Single Images | 2025 | Paper Website |














































































































































































































































