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Datasets:
InSAI-Lab
/
Trans4Map

Tasks:
Image Segmentation
Sub-tasks:
semantic-segmentation
Languages:
English
Size:
1K<n<10K
ArXiv:
Tags:
bird-eye-view
semantic-mapping
matterport3d
replica
bev-segmentation
wacv-2023
License:
Dataset card Files
xet
 Community
Trans4Map
File size: 2,874 Bytes
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---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license: apache-2.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- image-segmentation
task_ids:
- semantic-segmentation
pretty_name: Trans4Map Semantic Top-Down Ground Truth Maps
tags:
- bird-eye-view
- semantic-mapping
- matterport3d
- replica
- bev-segmentation
- wacv-2023
---

# Trans4Map Ground Truth Semantic Maps

Official dataset repository containing top-down semantic ground truth maps for **Trans4Map: Revisiting Holistic Bird's-Eye-View Mapping from Egocentric Images to Allocentric Semantics with Vision Transformers** (WACV 2023).

- **GitHub Repository:** [InSAI-Lab/Trans4Map](https://github.com/InSAI-Lab/Trans4Map)
- **Paper:** [arXiv:2207.06205](https://arxiv.org/abs/2207.06205)
- **Model Checkpoints:** [InSAI-Lab/Trans4Map (Model Zoo)](https://huggingface.co/InSAI-Lab/Trans4Map)
- **Collection:** [InSAI-Lab/Trans4Map & Egocentric Mapping](https://huggingface.co/collections/InSAI-Lab/trans4map-wacv-2023-6ad1f2a3c75d4b8e)

---

## Dataset Overview

Trans4Map benchmarks holistic top-down bird's-eye-view (BEV) semantic mapping from egocentric observations in indoor environments (Matterport3D & Replica).
This repository hosts the **top-down semantic ground truth maps (`.h5` files)** generated across Matterport3D environments following the Semantic-MapNet (SMNet) protocol.

### Directory Structure

```text
data/
└── semmap/
    ├── 17DRP5sb8fy_0.h5
    ├── 1LXtFkjw3qL_0.h5
    ├── 1LXtFkjw3qL_1.h5
    ├── ... (87 scene ground truth .h5 files)
    └── zsNo4HB9uLZ_0.h5
```

Alternatively, download the full archive `semmap.tar.gz`.

---

## Download Instructions

### Using Hugging Face CLI:

```bash
# Download the consolidated tar.gz archive
hf download InSAI-Lab/Trans4Map semmap.tar.gz --type dataset --local-dir ./data

# Extract to data/semmap
tar -zxvf ./data/semmap.tar.gz -C ./data
```

### Using Python (`huggingface_hub`):

```python
from huggingface_hub import hf_hub_download
import tarfile

tar_path = hf_hub_download(
    repo_id="InSAI-Lab/Trans4Map",
    filename="semmap.tar.gz",
    repo_type="dataset",
    local_dir="./data"
)
with tarfile.open(tar_path, "r:gz") as tar:
    tar.extractall("./data")
```

---

## Citation

```bibtex
@inproceedings{chen2023trans4map,
  title={Trans4Map: Revisiting Holistic Bird's-Eye-View Mapping from Egocentric Images to Allocentric Semantics with Vision Transformers},
  author={Chen, Chang and Zhang, Jiaming and Yang, Kailun and Peng, Kunyu and Stiefelhagen, Rainer},
  booktitle={2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
  year={2023}
}
```

## License

This dataset is released under the [Apache-2.0 License](https://www.apache.org/licenses/LICENSE-2.0).