Add dataset card for GS3LAM

README.md

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+---
+license: other
+task_categories:
+- image-segmentation
+---
+
+# GS3LAM: Gaussian Semantic Splatting SLAM
+
+This dataset repository contains the semantic labels and processed data associated with the paper [GS3LAM: Gaussian Semantic Splatting SLAM](https://huggingface.co/papers/2603.27781).
+
+GS3LAM is a Gaussian Semantic Splatting SLAM framework that processes multimodal data (RGB, depth, and semantics) to render consistent, dense semantic maps in real-time. This repository primarily provides semantic labels for existing benchmarks where they were previously unavailable or required consistent processing.
+
+- **Project Page:** [https://lif314.github.io/projects/gs3lam/](https://lif314.github.io/projects/gs3lam/)
+- **Repository:** [https://github.com/lif314/GS3LAM](https://github.com/lif314/GS3LAM)
+- **Paper:** [arXiv:2603.27781](https://arxiv.org/abs/2603.27781)
+
+## Dataset Description
+
+The project utilizes and provides enhancements for several SLAM benchmarks:
+
+- **Replica:** The original Replica dataset lacks semantic labels. This version includes semantic labels obtained from vMAP to enable semantic SLAM evaluation.
+- **TUM-RGBD:** Includes pseudo-semantic labels generated by DEVA for the `freiburg1_desk` sequence to evaluate semantic consistency in real-world scenarios.
+- **ScanNet:** Uses standard sequences (e.g., `scene0000_00`, `scene0059_00`) for benchmarking tracking and reconstruction.
+
+## Usage
+
+To use this dataset with the GS3LAM framework, please follow the installation instructions in the [official GitHub repository](https://github.com/lif314/GS3LAM).
+
+Example command to run GS3LAM on a Replica scene:
+
+```bash
+python run.py configs/Replica/office0.py
+```
+
+## Citation
+
+```bibtex
+@inproceedings{li2024gs3lam,
+      author = {Li, Linfei and Zhang, Lin and Wang, Zhong and Shen, Ying},
+      title = {GS3LAM: Gaussian Semantic Splatting SLAM},
+      year = {2024},
+      publisher = {Association for Computing Machinery},
+      address = {New York, NY, USA},
+      booktitle = {Proceedings of the 32nd ACM International Conference on Multimedia},
+      pages = {3019–3027},
+      numpages = {9},
+      location = {Melbourne VIC, Australia},
+      series = {MM '24}
+}
+```
+
+## License
+This work relies on SplaTAM; please adhere to the guidelines set forth in the [SplaTAM license](https://github.com/spla-tam/SplaTAM/blob/main/LICENSE).