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dfki-av/
ReLaGS

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ReLaGS: Relational Language Gaussian Splatting

This repository contains the official Hugging Face model release for ReLaGS (CVPR 2026).

Project page: https://dfki-av.github.io/ReLaGS/

Overview

ReLaGS is a framework for open-vocabulary 3D scene understanding built on top of Gaussian Splatting reconstructions.

It combines:

A Graph Neural Network (GNN) trained on 3RScan for predicting open-vocabulary relations in 3D scene graphs
A set of Gaussian Splatting reconstructed scenes enriched with open-vocabulary semantic features

The release is intended for evaluation and reproducibility of open-vocabulary scene graph reasoning in reconstructed 3D scenes.

Repository Structure

1. GNN Model (`GNN_model/`)

This directory contains a pretrained Graph Neural Network for predicting open-vocabulary relations in 3D scene graphs.

Training data:

3RScan dataset

Task:

Given a scene graph with object-level nodes, predict:

Pairwise relations between objects
Open-vocabulary relation labels (language-based)

Inputs:

Node features (geometry + appearance + learned embeddings)
Scene graph structure (nodes + edges)

Outputs:

Directed edges with predicted relation labels

2. Scenes (`scenes/`)

This directory contains reconstructed Gaussian Splatting scenes (based on LeRF-style reconstructions) augmented with semantic features.

Citation

If you find ReLaGS useful for your research, please cite:

bibtex

@inproceedings{xiearafa2026relags,
  title     = {ReLaGS: Relational Language Gaussian Splatting},
  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},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2026}
}

dfki-av/ReLaGS