Seungjun Lee ·
Zihan Wang ·
Yunsong Wang ·
Gim Hee Lee
National University of Singapore
Build and understand at Once! By taking over 300 streaming images, our EmbodiedSplat reconstructs whole-scene open-vocabulary 3DGS in online manner at up to 5-6 FPS per-frame processing time. Reconstructed scene supports diverse perception tasks such as open-vocabulary 3D semantic segmentation, 2D-rendered semantic segmentation and novel-view color synthesis with depth rendering.
## Citation If you find our code or paper useful, please cite ```bibtex @article{lee2026embodiedsplat, title={EmbodiedSplat: Online Feed-Forward Semantic 3DGS for Open-Vocabulary 3D Scene Understanding}, author={Lee, Seungjun and Wang, Zihan and Wang, Yunsong and Lee, Gim Hee}, journal={arXiv preprint arXiv:2603.04254}, year={2026} } ```