| ---
|
| license: cc-by-4.0
|
| pretty_name: MedPhyGraph Procedural Support-Graph Data
|
| viewer: false
|
| tags:
|
| - digital-twins
|
| - scene-graphs
|
| - support-relations
|
| - counterfactual-evidence
|
| - structured-scene-states
|
| - procedural
|
| - robotics
|
| - reproducibility
|
| ---
|
|
|
| # MedPhyGraph — Procedural Support-Graph Data
|
|
|
| Structured procedural training and evaluation data for:
|
|
|
| **MedPhyGraph: Counterfactual Support-Graph Maintenance for Dynamic Built-Environment Digital Twins**
|
| *TwinWorld: Visual Intelligence for Built Environment Digital Twins, ECCV 2026 Workshop*
|
|
|
| This repository contains the procedural data released with MedPhyGraph,
|
| including the candidate-edge data used with
|
| [CF-SupportNet](https://huggingface.co/MedPhyGraph/CF-SupportNet) and the
|
| structured procedural scenes used in the public evaluation workflows.
|
|
|
| MedPhyGraph is a **method contribution**, not a dataset or benchmark
|
| contribution. This repository is provided to make the released experiments
|
| easier to inspect, reuse, and reproduce.
|
|
|
| | Resource | Link |
|
| |---|---|
|
| | Paper | [openreview.net/forum?id=McTaO1qM8H](https://openreview.net/forum?id=McTaO1qM8H) |
|
| | Dataset | **You are here** |
|
| | Code | [github.com/kamranghz/medphygraph](https://github.com/kamranghz/medphygraph) |
|
| | Model | [MedPhyGraph/CF-SupportNet](https://huggingface.co/MedPhyGraph/CF-SupportNet) |
|
| | Project | [medphygraph.github.io](https://medphygraph.github.io/) |
|
|
|
| ## At a glance
|
|
|
| | Item | Public release |
|
| |---|---|
|
| | Candidate-edge samples | **533** |
|
| | Train / validation / test | **324 / 101 / 108** |
|
| | Procedural scene states | **54** |
|
| | Procedural transfer cases | **136** |
|
| | Full expanded suite reported in the paper | **217 cases** |
|
| | Isaac for Healthcare cases included here | **0** |
|
| | License | **CC BY 4.0** |
|
|
|
| The paper evaluates **217 expanded transfer cases** in total:
|
|
|
| - **136 Procedural**
|
| - **81 Isaac for Healthcare**
|
|
|
| This repository contains the **136 Procedural cases only**.
|
| The 81 Isaac for Healthcare cases are not redistributed here.
|
|
|
| ---
|
|
|
| ## Download
|
|
|
| The easiest way to download the complete public release is with the
|
| Hugging Face CLI:
|
|
|
| ```bash
|
| hf download MedPhyGraph/support-graph-data \
|
| --repo-type dataset \
|
| --local-dir ./support-graph-data
|
| ```
|
|
|
| Or with Python:
|
|
|
| ```python
|
| from huggingface_hub import snapshot_download
|
|
|
| snapshot_download(
|
| repo_id="MedPhyGraph/support-graph-data",
|
| repo_type="dataset",
|
| local_dir="./support-graph-data",
|
| )
|
| ```
|
|
|
| Both methods download the complete public release while preserving its
|
| directory structure.
|
|
|
| Individual artifacts can also be inspected from the **Files and versions** tab
|
| on Hugging Face.
|
|
|
| > **Dataset Viewer**
|
| >
|
| > The Hugging Face Dataset Viewer is intentionally disabled. This release
|
| > preserves the original scientific JSON artifacts, and different directories
|
| > contain different JSON schemas. We keep those artifacts in their frozen form
|
| > rather than reshaping them only for a tabular viewer.
|
|
|
| ---
|
|
|
| ## Contents
|
|
|
| | Released directory | Contains | Expected MedPhyGraph path |
|
| |---|---|---|
|
| | `training_data/` | Frozen CF-SupportNet candidate-edge dataset and split | `outputs/dyphygraph_health/dataset_hard/` |
|
| | `procedural_scenes/` | Structured Procedural scene states and transition metadata | `outputs/dyphygraph_health/scenes_twinworld_phase2/` |
|
| | `expanded_transfer_procedural_v1/` | 136 Procedural transfer cases, targets, and before/after states | `outputs/reviewer_response/expanded_transfer_v1/` |
|
|
|
| > **Note:** the release directory is named
|
| > `expanded_transfer_procedural_v1/`, while the public evaluation scripts expect
|
| > its contents under `outputs/reviewer_response/expanded_transfer_v1/`.
|
|
|
| ### `training_data/`
|
|
|
| Contains:
|
|
|
| - `dataset.json`
|
| - `split.json`
|
|
|
| The frozen dataset contains **533 candidate-edge samples**:
|
|
|
| - Train: **324**
|
| - Validation: **101**
|
| - Test: **108**
|
|
|
| The samples come from procedurally authored scenes and use the analytic
|
| **AABB host-removal counterfactual evidence** protocol used by CF-SupportNet.
|
|
|
| The analytic backend is a geometric proxy and should not be interpreted as a
|
| full physics-engine simulation.
|
|
|
| No Isaac-derived samples are included.
|
|
|
| ### `procedural_scenes/`
|
|
|
| Contains the structured Procedural evaluation states released with MedPhyGraph.
|
|
|
| The public release includes:
|
|
|
| - **54 `scene.json` states**
|
| - scene indexes
|
| - transition metadata
|
| - procedural AABB proxy geometry
|
|
|
| These states are used by the public procedural evaluation workflow and can also
|
| be used to regenerate intermediate procedural data required by some evaluation
|
| scripts.
|
|
|
| ### `expanded_transfer_procedural_v1/`
|
|
|
| Contains the public Procedural portion of the expanded transfer evaluation:
|
|
|
| - **136 transfer cases**
|
| - **272 before/after `scene.json` files**
|
| - `predeclared_manifest.json`
|
| - `targets.json`
|
| - `scenes/procedural/`
|
|
|
| This directory is **not the complete 217-case suite reported in the paper**.
|
| It contains the 136 Procedural cases only.
|
|
|
| For use with the public evaluation scripts, place its contents under:
|
|
|
| ```text
|
| outputs/reviewer_response/expanded_transfer_v1/
|
| ```
|
|
|
| so that the resulting layout contains:
|
|
|
| ```text
|
| outputs/reviewer_response/expanded_transfer_v1/
|
| ├── predeclared_manifest.json
|
| ├── targets.json
|
| └── scenes/
|
| └── procedural/
|
| ```
|
|
|
| ---
|
|
|
| ## What is not included
|
|
|
| This repository does **not** redistribute:
|
|
|
| - NVIDIA Isaac for Healthcare assets
|
| - NVIDIA Isaac Sim USD / USDA / USDC files
|
| - NVIDIA meshes or textures
|
| - Isaac-derived structured scene states
|
| - the 81 Isaac for Healthcare transfer cases reported in the paper
|
|
|
| These resources are intentionally kept outside the public MedPhyGraph dataset
|
| release.
|
|
|
| ---
|
|
|
| ## NVIDIA Isaac for Healthcare
|
|
|
| The MedPhyGraph paper also evaluates the method in
|
| **NVIDIA Isaac for Healthcare** environments.
|
|
|
| To work with the Isaac portion of MedPhyGraph, users should obtain NVIDIA Isaac
|
| Sim / Isaac for Healthcare and the required assets directly from NVIDIA under
|
| the applicable NVIDIA license terms.
|
|
|
| ### Official NVIDIA resources
|
|
|
| | Resource | Official link |
|
| |---|---|
|
| | NVIDIA Isaac for Healthcare | [developer.nvidia.com/isaac/healthcare](https://developer.nvidia.com/isaac/healthcare) |
|
| | Getting Started | [NVIDIA documentation](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-for-healthcare/latest/index.html) |
|
| | Setup Guide | [NVIDIA setup instructions](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-for-healthcare/latest/training-healthcare-robots-from-scratch/01-setup/01-setup.html) |
|
| | Loading Assets | [NVIDIA asset-loading guide](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-for-healthcare/latest/training-healthcare-robots-from-scratch/02-data-loading/02-loading-custom-assets.html) |
|
| | Isaac for Healthcare GitHub | [github.com/isaac-for-healthcare](https://github.com/isaac-for-healthcare) |
|
| | i4h Workflows | [isaac-for-healthcare/i4h-workflows](https://github.com/isaac-for-healthcare/i4h-workflows) |
|
|
|
| MedPhyGraph does not repackage or redistribute NVIDIA-authored assets. Users
|
| obtain those resources directly from NVIDIA and work with them locally.
|
|
|
| ---
|
|
|
| ## Reproducibility
|
|
|
| The public release supports several procedural evaluation workflows, but it is
|
| important to distinguish between re-running the released evaluations and
|
| regenerating every paper artifact from scratch.
|
|
|
| ### Procedural evaluation
|
|
|
| The following public artifacts are available:
|
|
|
| - the frozen **533-sample** candidate-edge dataset and split
|
| - the **54** structured Procedural scene states
|
| - the **136-case** Procedural expanded-transfer subset
|
| - the paper-frozen
|
| [CF-SupportNet checkpoints](https://huggingface.co/MedPhyGraph/CF-SupportNet)
|
| - the corresponding public MedPhyGraph evaluation code
|
|
|
| With these artifacts, users can re-run evaluation using the released
|
| candidate-edge dataset and paper-frozen CF-SupportNet checkpoints, and
|
| re-evaluate the public 136-case Procedural expanded-transfer subset.
|
|
|
| Some core procedural paper tables additionally require an intermediate file:
|
|
|
| ```text
|
| outputs/dyphygraph_health/dataset_twinworld_phase2/dataset.json
|
| ```
|
|
|
| That intermediate dataset is **not included directly** in this Hugging Face
|
| release.
|
|
|
| The corresponding structured Phase-2 procedural scenes are included under
|
| `procedural_scenes/`, and the public MedPhyGraph code contains the
|
| data-generation components needed for this workflow.
|
|
|
| For this reason, this repository should be understood as the frozen public data
|
| release supporting the Procedural evaluation workflows, rather than as a
|
| one-command reproduction package for every paper table.
|
|
|
| ### Isaac for Healthcare evaluation
|
|
|
| The Isaac portion additionally requires:
|
|
|
| 1. NVIDIA Isaac Sim / Isaac for Healthcare
|
| 2. the required NVIDIA assets obtained separately from NVIDIA
|
| 3. MedPhyGraph Isaac-facing scene-generation and evaluation components
|
|
|
| The public MedPhyGraph code includes relevant components for working with
|
| locally installed Isaac environments. However, the complete paper-frozen Isaac
|
| scene-generation workflow is not currently packaged as a standalone end-to-end
|
| public pipeline.
|
|
|
| The structured states used for the paper's **81 Isaac cases** are also not
|
| redistributed in this repository.
|
|
|
| Therefore, the exact Isaac results reported in the paper should **not** be
|
| expected to reproduce from the currently released public artifacts alone.
|
|
|
| ---
|
|
|
| ## Relationship to CF-SupportNet
|
|
|
| [CF-SupportNet](https://huggingface.co/MedPhyGraph/CF-SupportNet) is the learned
|
| candidate-edge scorer used within MedPhyGraph.
|
|
|
| The model repository contains five paper-frozen checkpoints:
|
|
|
| - **seed 0** — primary paper checkpoint
|
| - **seeds 1–4** — multi-seed reproducibility checkpoints
|
|
|
| MedPhyGraph itself is broader than CF-SupportNet.
|
|
|
| In addition to the learned scorer, MedPhyGraph applies deterministic
|
| **State Consistency** and **Union-Based Transition-Aware Consistency** to
|
| maintain support relations across adjacent digital-twin states.
|
|
|
| These deterministic components are part of the MedPhyGraph inference pipeline
|
| and are not separate learned checkpoints. The full reference implementation is
|
| on GitHub: [kamranghz/medphygraph](https://github.com/kamranghz/medphygraph).
|
|
|
| ---
|
|
|
| ## Integrity
|
|
|
| Two files are provided for release verification:
|
|
|
| - **`MANIFEST.json`** — index and metadata for the released public artifacts
|
| - **`SHA256SUMS.txt`** — per-artifact SHA256 hashes for integrity checking
|
|
|
| These files can be used to verify the released scientific artifacts in a local
|
| copy.
|
|
|
| ---
|
|
|
| ## License
|
|
|
| The MedPhyGraph-owned content in this repository is released under the
|
| **Creative Commons Attribution 4.0 International License (CC BY 4.0)**.
|
|
|
| NVIDIA Isaac for Healthcare assets are **not included** in this repository and
|
| are not being relicensed by MedPhyGraph. NVIDIA resources remain subject to
|
| NVIDIA's own license terms.
|
|
|
| ---
|
|
|
| ## Citation
|
|
|
| Paper: [https://openreview.net/forum?id=McTaO1qM8H](https://openreview.net/forum?id=McTaO1qM8H)
|
|
|
| If you use MedPhyGraph or these released artifacts, please cite:
|
|
|
| ```bibtex
|
| @inproceedings{hamlabadi2026medphygraph,
|
| title = {MedPhyGraph: Counterfactual Support-Graph Maintenance for Dynamic Built-Environment Digital Twins},
|
| author = {Kamran Gholizadeh HamlAbadi and Monica Vahdati and Abdulmotaleb El Saddik},
|
| booktitle = {[Archival Track] ECCV 2026 TwinWorld: 1st Workshop on Visual Intelligence for Built Environment Digital Twins},
|
| year = {2026},
|
| url = {https://openreview.net/forum?id=McTaO1qM8H}
|
| }
|
| ``` |
