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LL3M writes Python code that generates 3D assets in Blender.
Official Torch/CUDA Implementation of Faithful Contouring
A procedural Blender pipeline for photorealistic training image generation
[SIGGRAPH Asia 2025] OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesion
An example that complies and runs the fast winding number for soups
PartSAM: A Scalable Promptable Part Segmentation Model Trained on Native 3D Data
[CVPR'25 Highlight] Official repository of Sonata: Self-Supervised Learning of Reliable Point Representations
Hunyuan 3D Part Segmentation and Generation Pipeline
[NeurIPS'25 Spotlight] GeoSVR: Taming Sparse Voxels for Geometrically Accurate Surface Reconstruction
A Unified Library for Parameter-Efficient and Modular Transfer Learning
From Images to High-Fidelity 3D Assets with Production-Ready PBR Material
Open Overleaf/ShareLaTex projects in vscode, with full collaboration support.
High quality training free inpaint for every stable diffusion model. Supports ComfyUI
[ICCV2025] GARF: Learning Generalizable 3D Reassembly for Real-World Fractures
[3DV 2026] FastMesh: Efficient Artistic Mesh Generation via Component Decoupling
[3DV 2026 Oral] VoxHammer: Training-Free Precise and Coherent 3D Editing in Native 3D Space
[ICLR2025, ICML2025, NeurIPS2025 Spotlight] Quantized Attention achieves speedup of 2-5x compared to FlashAttention, without losing end-to-end metrics across language, image, and video models.
🔥🔥🔥Official Codebase of "DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape Generation"
Implementation of MeshGPT, SOTA Mesh generation using Attention, in Pytorch
The simplest, fastest repository for training/finetuning medium-sized GPTs.
An implementation of model parallel autoregressive transformers on GPUs, based on the Megatron and DeepSpeed libraries
[NeurIPS 2024] MeshXL: Neural Coordinate Field for Generative 3D Foundation Models, a 3D fundamental model for mesh generation
Inside-Outside Segmentation using Fast Winding Numbers Approximation
[ECCV 2024 Best Paper Candidate & TPAMI 2025] PointLLM: Empowering Large Language Models to Understand Point Clouds
Reference PyTorch implementation and models for DINOv3