| --- |
| pretty_name: ImagiRep |
| license: other |
| license_name: imagirep-license |
| license_link: LICENSE.md |
| language: |
| - en |
| task_categories: |
| - visual-question-answering |
| - multiple-choice |
| tags: |
| - spatial-reasoning |
| - world-models |
| - visual-imagination |
| - matterport3d |
| - benchmark |
| size_categories: |
| - n<1K |
| extra_gated_heading: "Access to ImagiRep requires agreeing to the Matterport3D Terms of Use" |
| extra_gated_prompt: >- |
| ImagiRep contains images, videos and geometry rendered from the Matterport3D dataset. |
| Before requesting access, you must have read and agreed to the Matterport3D Terms of Use |
| (https://kaldir.vc.in.tum.de/matterport/MP_TOS.pdf). The data may be used for non-commercial |
| academic research only and may not be redistributed. |
| extra_gated_fields: |
| Name: text |
| Affiliation: text |
| I have agreed to the Matterport3D Terms of Use: checkbox |
| I will use ImagiRep for non-commercial research only and will not redistribute it: checkbox |
| configs: |
| - config_name: questions |
| data_files: |
| - split: test |
| path: benchmark/benchmark922/questions.jsonl |
| --- |
| |
| # ImagiRep |
|
|
| Benchmark data for the paper |
| **Representing the Unseen: Rethinking Visual Imagination for Spatial Reasoning** |
| (Zengqi Zhao\*, Zun Wang\*, Shoubin Yu, Mohit Bansal, Yue Zhang; UNC Chapel Hill; \* equal contribution). |
|
|
| [Project page](https://imagirep.github.io/) · [Paper (arXiv)](https://arxiv.org/abs/2610.37437) · |
| [Code and results (GitHub)](https://github.com/Imagirep/ImagiRep) |
|
|
| ImagiRep has 922 four-option spatial reasoning questions about unobserved viewpoints in Matterport3D scenes: |
|
|
| | setting | questions | groups | scenes | question types | |
| |---|---:|---:|---:|---| |
| | Viewpoint Imagination | 622 | 200 trajectories | 73 | Open-space Direction (91), Nearest-obstacle Direction (55), Visibility (104), Nearest Object (104), Farthest Object (98), Object-relative Direction (170) | |
| | Cross-view Integration | 300 | 143 view groups | 21 | Nearest Object (81), Farthest Object (82), Spatial Ordering (137) | |
|
|
| For every question the imagined (unobserved) state is given as endpoint RGB and six alternative representations of |
| the same state: top-down geometry, spatial text, video, depth, surface normals and panorama. The dataset also holds the |
| estimated representations used in the paper (from HY-World 2.0 for Viewpoint Imagination, and from Stable Virtual Camera |
| with MoGe-2 depth for Cross-view Integration). |
|
|
| ## Contents |
|
|
| | path | content | |
| |---|---| |
| | `benchmark/benchmark922/questions.jsonl` | 922 rows: question, options, gold answer, system prompt, and the evidence of every input condition | |
| | `benchmark/benchmark922/tasks.jsonl` | 7,376 model-ready requests (922 questions x 8 conditions) as ordered parts `{"text"}`, `{"image"}`, `{"video"}` | |
| | `benchmark/benchmark922/images/`, `videos/` | all images and videos referenced by the two files above; `SHA256SUMS` | |
| | `benchmark/uid_lists_and_index/` | uid lists and `question_index.tsv` (category, gold, trajectory or view group, scan, look-back flag) | |
| | `benchmark/camera_poses/` | camera poses and Matterport3D scan / viewpoint ids for every question | |
| | `benchmark/randomization/` | how each question was randomized from its annotation (option order; image numbering for Cross-view Integration) | |
| | `03_estimated_viewpoint_gpt61sol/` | estimated representations for Viewpoint Imagination: `estimated_assets/` and the exact request images `gpt_runs/images/` | |
| | `04_estimated_crossview_gpt61sol/` | estimated RGB and depth for Cross-view Integration: `gpt_runs/inputs/` and `gpt_runs/images/` | |
|
|
| The folders follow the layout of the GitHub repository: clone it and download this dataset into its root, and the |
| scripts there find every file (`hf download Imagirep/ImagiRep --repo-type dataset --local-dir .`). |
| The request files and per-question model outputs that use the estimated images are in the GitHub repository. |
|
|
| Input conditions: `observed` (observed view(s)), `oracle` (+ endpoint RGB; for look-back questions a view from the |
| endpoint facing the start) and `oracle_<m>` (+ one representation `m`: `topdown`, `text`, `video`, `depth`, |
| `surface_normals`, `panorama`). |
|
|
| ```python |
| import json |
| qs = [json.loads(l) for l in open("benchmark/benchmark922/questions.jsonl")] |
| q = qs[0] |
| print(q["uid"], q["category"], q["gold"]) |
| print(q["question_prompt"]) |
| print(q["conditions"]["oracle_panorama"]) # text parts and file names in images/ and videos/ |
| ``` |
|
|
| ## License and terms |
|
|
| See `LICENSE.md`. Images, videos and geometry are derived from Matterport3D and remain subject to the Matterport3D |
| Terms of Use: non-commercial academic research only, no redistribution. Questions, labels and other annotations are |
| released under CC BY-NC 4.0. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{zhao2026imagirep, |
| title = {Representing the Unseen: Rethinking Visual Imagination for Spatial Reasoning}, |
| author = {Zhao, Zengqi and Wang, Zun and Yu, Shoubin and Bansal, Mohit and Zhang, Yue}, |
| journal = {arXiv preprint arXiv:2610.37437}, |
| year = {2026} |
| } |
| ``` |
|
|
