FUS3DMaps: Dual-Layer Open-Vocabulary Semantic Mapping for Robots
FUS3DMaps presents an innovative online semantic mapping technique that integrates dense and instance-level open-vocabulary layers into a unified voxel map. This dual-layer framework facilitates voxel-level semantic fusion of layer embeddings, leveraging the unique advantages of both methods. It overcomes the scalability challenges faced by current training-free approaches that depend on multi-view fusion of semantic embeddings. By utilizing complete uncropped image frames, FUS3DMaps avoids the need for segmentation and 2D-to-3D instance linking. The study, which proposes a cross-layer semantic fusion method, can be found on arXiv under the identifier 2605.03669.
Key facts
- FUS3DMaps is an online dual-layer semantic mapping method.
- It jointly maintains dense and instance-level open-vocabulary layers.
- The layers are within a shared voxel map.
- It enables voxel-level semantic fusion of layer embeddings.
- The method combines complementary strengths of both semantic mapping approaches.
- It addresses scalability limitations of existing training-free methods.
- Existing methods rely on multi-view fusion of semantic embeddings.
- FUS3DMaps operates on full uncropped image frames.
- It sidesteps segmentation and 2D-to-3D instance association.
- The paper is published on arXiv with ID 2605.03669.
Entities
Institutions
- arXiv