| --- |
| pretty_name: "TranSpace — playroom_drjohnson" |
| license: other |
| license_name: non-commercial-research |
| license_link: https://github.com/codeshim/transpace/blob/main/LICENSE |
| tags: |
| - 3d-reconstruction |
| - novel-view-synthesis |
| - scene-synthesis |
| - indoor-scenes |
| size_categories: |
| - 10B<n<100B |
| --- |
| |
| # TranSpace — `playroom_drjohnson` data pack |
| |
| Data for the released demo of: |
| |
| > **TranSpace: Progressive Anchoring for Metric-Consistent Scene Synthesis** |
| > Hyeshim Kim, Taehei Kim\*, Jihun Shin\*, Hyeonjin Kim, Sung-Hee Lee — *\*equal contribution* |
| > KAIST · ACM Multimedia 2026 (MM '26) |
| > [doi:10.1145/3767308.3836316](https://doi.org/10.1145/3767308.3836316) |
| |
| Code: https://github.com/codeshim/transpace |
| |
| TranSpace synthesizes the transition geometry between two separately captured |
| indoor scenes. This pack contains everything the pipeline needs to reproduce that |
| for the Deep Blending `playroom` and `drjohnson` rooms: the two reconstructed |
| rooms, the inpainted keyframes, and every intermediate video. The demo replays |
| these, so no generative model or API key is required. |
| |
| ## Download |
| |
| ```bash |
| pip install huggingface_hub |
|
|
| # everything (~19 GB) |
| hf download codeshim/transpace-playroom-drjohnson --repo-type dataset \ |
| --local-dir data/playroom_drjohnson |
| ``` |
| |
| Place it at `data/playroom_drjohnson/` inside the code repository, then: |
|
|
| ```bash |
| python main.py |
| ``` |
|
|
| ## Contents |
|
|
| ``` |
| playroom_drjohnson/ |
| ├── playroom_aligned/ room A: images/, sparse/, checkpoints/ |
| ├── drjohnson_aligned/ room B: images/, sparse/, checkpoints/ |
| ├── BASE_model/ floor/threshold voxel model |
| ├── trspace_padding_model_type{0,1,2}/ space_id mask model per variant |
| ├── trspace_source_type{0,1,2}/ inpainted keyframes + intermediate videos |
| └── playroom_drjohnson_alignment_info_type{0,1,2}.json |
| ``` |
|
|
| Each room directory is self-contained: its COLMAP reconstruction (`images/`, |
| `sparse/`) and its trained SVRaster voxel model (`checkpoints/`) side by side. |
|
|
| Three connector variants are provided for the same room pair — `type0` (wing |
| wall), `type1` (pony wall), `type2` (internal window). Only the RIGHT connector |
| varies; LEFT is an internal window in every variant. A variant's source videos, |
| alignment info and padding model must be used together. |
|
|
| `trspace_source_type*/` holds the inputs that were generated offline: |
|
|
| | | | |
| |---|---| |
| | `<VIEW>_generated.png` | inpainted keyframe | |
| | `<VIEW>_depth_raw.npy` | its aligned metric depth | |
| | `<START>_<END>_iterNN.mp4` | per-iteration transition video | |
| | `<START>_<END>_iterNN_f2m.mp4` / `_m2b.mp4` | final-closing segment videos | |
|
|
| ## Provenance and licensing |
|
|
| Derived from the **Deep Blending** scenes `drjohnson` and `playroom`: |
|
|
| > Deep Blending for Free-Viewpoint Image-Based Rendering. |
| > Hedman, Philip, Price, Frahm, Drettakis, Brostow. *ACM ToG* 37(6), 2018. |
|
|
| The keyframes were produced with Google Vertex AI Imagen 2 (since retired) and |
| the intermediate videos with DeeVid AI Video Generation V2.1. |
|
|
| **Non-commercial use only** (research or evaluation). The voxel models are |
| produced by [SVRaster](https://github.com/NVlabs/svraster), whose license limits |
| the work and its derivatives to non-commercial use. |
|
|
| The paper additionally evaluates on ScanNet++ scenes, which are **not** |
| redistributed here. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{kim2026transpace, |
| title = {TranSpace: Progressive Anchoring for Metric-Consistent Scene Synthesis}, |
| author = {Kim, Hyeshim and Kim, Taehei and Shin, Jihun and Kim, Hyeonjin and Lee, Sung-Hee}, |
| booktitle = {Proceedings of the 34th ACM International Conference on Multimedia (MM '26)}, |
| year = {2026}, |
| publisher = {ACM}, |
| doi = {10.1145/3767308.3836316} |
| } |
| ``` |
|
|
