SaaF: Scene-Specific Ambiguity-Aware 3D Language Fields for Interactive Object Retrieval
Researchers introduce SaaF, a novel 3D language field based on Gaussian Splatting, designed to improve interactive object retrieval in real-world scenes using natural language. SaaF addresses limitations of prior methods by employing metric learning to enhance instance discrimination and by training on multiple text labels, including ambiguous descriptions, to better handle ambiguous queries. Experiments show that SaaF achieves higher retrieval accuracy and can robustly detect and manage ambiguity in user queries.
Why it matters: This work represents a meaningful advance in enabling service robots to more accurately and interactively retrieve objects in complex environments using natural language, even when queries are ambiguous.
Full story at: arXiv Computer Vision ↗