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| license: cc-by-nc-4.0
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| # ReLaGS: Relational Language Gaussian Splatting
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| This repository contains the official Hugging Face model release for **ReLaGS (CVPR 2026)**.
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| Project page: https://dfki-av.github.io/ReLaGS/
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| ---
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| ## Overview
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| **ReLaGS** is a framework for **open-vocabulary 3D scene understanding** built on top of Gaussian Splatting reconstructions.
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| It combines:
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| - A **Graph Neural Network (GNN)** trained on **3RScan** for predicting open-vocabulary relations in 3D scene graphs
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| - A set of **Gaussian Splatting reconstructed scenes** enriched with **open-vocabulary semantic features**
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| The release is intended for **evaluation and reproducibility** of open-vocabulary scene graph reasoning in reconstructed 3D scenes.
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| ## Repository Structure
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| ## 1. GNN Model (`GNN_model/`)
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| This directory contains a pretrained **Graph Neural Network** for predicting **open-vocabulary relations** in 3D scene graphs.
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| ### Training data:
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| - 3RScan dataset
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| ### Task:
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| Given a scene graph with object-level nodes, predict:
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| - Pairwise relations between objects
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| - Open-vocabulary relation labels (language-based)
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| ### Inputs:
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| - Node features (geometry + appearance + learned embeddings)
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| - Scene graph structure (nodes + edges)
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| ### Outputs:
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| - Directed edges with predicted relation labels
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| ---
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| ## 2. Scenes (`scenes/`)
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| This directory contains reconstructed **Gaussian Splatting scenes** (based on LeRF-style reconstructions) augmented with semantic features.
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| ---
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| ## Citation
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| If you find ReLaGS useful for your research, please cite:
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| ```bibtex
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| @inproceedings{xiearafa2026relags,
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| title = {ReLaGS: Relational Language Gaussian Splatting},
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| author = {Xie, Yaxu and Arafa, Abdalla and Javanmardi, Alireza and Millerdurai, Christen and Hu, Jia Cheng and Wang, Shaoxiang and Pagani, Alain and Stricker, Didier},
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| booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
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| year = {2026}
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| }
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| ``` |
