Datasets:
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pretty_name: Type1b Multi-View Spatial Reasoning
language:
- en
task_categories:
- visual-question-answering
tags:
- multi-view
- 3d
- spatial-reasoning
- synthetic-data
---
# Type1b Multi-View Spatial Reasoning
Type1b contains gravity-settled Blender scenes, 26-view RGB renders, auditable
spatial QA, and raw model predictions. Four vertical-spread conditions are
released under the uniform names `zspread_025`, `zspread_050`, `zspread_075`,
and `zspread_100`.
Generation, evaluation, and analysis code is available in the
[DM3SR GitHub repository](https://github.com/Ever2after/DM3SR).
## Dataset layout
```text
scenes/zspread_XXX/ scene JSON and validation metadata
physics/zspread_XXX/ settled physics reports
renders/zspread_XXX/ 26-view PNGs and render_report.json
qa/zspread_XXX/ canonical QA JSONL
qa_ablation/view_count/zspread_XXX/ paired 2--6 input-view controls
evaluation/zspread_XXX/ model predictions and scores
evaluation/view_count/zspread_100/ input-view-count predictions
metadata/evaluation_lineage.json QA/input-image lineage audit
```
The main tasks are `object_counting`, `relative_distance`, and
`relative_position`. QA rows reference images relative to their corresponding
`renders/zspread_XXX` directory.
## Canonical render counts
| Level | Scenes | PNGs |
|---|---:|---:|
| zspread_025 | 23 | 598 |
| zspread_050 | 31 | 806 |
| zspread_075 | 43 | 1,118 |
| zspread_100 | 41 | 1,066 |
Every released scene directory also contains `render_report.json`. The scene
specification collection contains 50 JSON files per level; Blender physics and
render validation determine the released render/QA subset.
## External assets
Scene specifications identify OmniObject3D assets by category and object ID.
Raw OmniObject3D scans and Poly Haven HDRIs are not redistributed in this
dataset; obtain them under their original licenses. The companion GitHub
repository contains category filters, HDRI checksums, generation, rendering,
QA, evaluation, and analysis code.
## Release integrity
Use `type1b/manifests/huggingface_dataset_manifest.json` in the companion code
repository for the exact local-source to Hub-destination mapping. The canonical
selection follows the QA `report_path` lineage rather than historical folder
labels, which avoids uploading an earlier unused z-spread render generation.
Some retained historical model runs evaluated the same counting questions with
an earlier random input-view selection, and some Qwen3 z=1.0 spatial files use
historical question IDs. Predictions embed their actual question and image list.
`metadata/evaluation_lineage.json` labels every file as exact, ID-remapped, or
same-content/different-input-views so these conditions are never conflated.
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