Monnte/shape-completion
3D Shape Completion - adaptation and improvement of DiffComplete model.
This project helps 3D artists, game developers, or designers reconstruct complete 3D models from incomplete or partially scanned data. You provide a 3D mesh or voxel representation with missing parts, and it generates a plausible, complete 3D shape. This is useful for anyone working with 3D models that are often incomplete due to scanning limitations or design stages.
No commits in the last 6 months.
Use this if you need to automatically fill in missing sections of 3D models, such as furniture, vehicles, or animals, to create fully realized objects.
Not ideal if you need to create entirely new 3D shapes from scratch or require extremely precise, engineering-grade reconstructions.
Stars
28
Forks
3
Language
Python
License
MIT
Category
Last pushed
Sep 28, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/Monnte/shape-completion"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
PRIS-CV/DemoFusion
Let us democratise high-resolution generation! (CVPR 2024)
mit-han-lab/distrifuser
[CVPR 2024 Highlight] DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models
Tencent-Hunyuan/HunyuanPortrait
[CVPR-2025] The official code of HunyuanPortrait: Implicit Condition Control for Enhanced...
giuvecchio/matfuse
MatFuse: Controllable Material Generation with Diffusion Models (CVPR2024)
Shilin-LU/TF-ICON
[ICCV 2023] "TF-ICON: Diffusion-Based Training-Free Cross-Domain Image Composition" (Official...