DermSynth3D
importeddata/dermsynth3d
Official code for "DermSynth3D: Synthesis of in-the-wild Annotated Dermatology Images". A data generation pipeline for creating photorealistic in-the-wild synthetic dermatalogical data with rich…
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Data & Standards
- Subcategory
- unknown
- License
- AGPL-3.0(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- sfu-mial
- Country
- unknown
- Homepage
- cvi2.uni.lu/3dbodytexdermsynth/
- Repository
- github.com/sfu-mial/DermSynth3D
- Documentation
- unknown
- Tags
- 3d-graphics · body-parser · deeplearning · dermatology · differentiable-rendering · human-anatomy · human-body-model · human-part-segmentation
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- DiffDRRdifferentiable-rendering
Auto-differentiable digitally reconstructed radiographs in PyTorch
- DiffPosedifferentiable-rendering
[CVPR 2024] Intraoperative 2D/3D registration via differentiable X-ray rendering
- Eidolon3d-graphics
Biomedical Visualization and Analysis Framework
- SAX-NeRF3d-graphics
"Structure-Aware Sparse-View X-ray 3D Reconstruction" (CVPR 2024) - A Toolbox for CT reconstruction and X-ray Novel View Synthesis
- AlbumentationsXdeeplearning
Next-generation Albumentations: dual-licensed for open-source and commercial use
- coursera-ai-for-medicine-specializationdeeplearning
Programming assignments, labs and quizzes from all courses in the Coursera AI for Medicine Specialization offered by deeplearning.ai
- api.github.com/repos/sfu-mial/DermSynth3Dretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2024-07-28, 30 stars, license reported as AGPL-3.0. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/8.json→ .entries["dermsynth3d"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.