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Found 6 papers, 1 papers with code
Open3DSG: Open-Vocabulary 3D Scene Graphs from Point Clouds with Queryable Objects and Open-Set Relationships
We co-embed the features from a 3D scene graph prediction backbone with the feature space of powerful open world 2D vision language foundation models.
Lang3DSG: Language-based contrastive pre-training for 3D Scene Graph prediction
While it is widely accepted that pre-training is an effective approach to improve model performance in low data regimes, in this paper, we find that existing pre-training methods are ill-suited for 3D scene graphs.
SGRec3D: Self-Supervised 3D Scene Graph Learning via Object-Level Scene Reconstruction
In the field of 3D scene understanding, 3D scene graphs have emerged as a new scene representation that combines geometric and semantic information about objects and their relationships.
Predicting Dense and Context-aware Cost Maps for Semantic Robot Navigation
The preliminary experiments suggest that the cost maps generated by our network are suitable for the MPC and can guide the agent to the semantic goal more efficiently than a baseline approach.
Cross-Modal Analysis of Human Detection for Robotics: An Industrial Case Study
We compare the performance of state-of-the-art person detectors for 2D range data, 3D lidar, and RGB-D data as well as selected combinations thereof in a challenging industrial use-case.
Multi-path Learning for Object Pose Estimation Across Domains
We introduce a scalable approach for object pose estimation trained on simulated RGB views of multiple 3D models together.
