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Found 4 papers, 0 papers with code
Segment Any Object Model (SAOM): Real-to-Simulation Fine-Tuning Strategy for Multi-Class Multi-Instance Segmentation
The foundational Segment Anything Model (SAM) is designed for promptable multi-class multi-instance segmentation but tends to output part or sub-part masks in the "everything" mode for various real-world applications.
What Is Near?: Room Locality Learning for Enhanced Robot Vision-Language-Navigation in Indoor Living Environments
We show that local-global planning based on locality knowledge and predicting the indoor layout allows the agent to efficiently select the appropriate action.
Artificial Empathy Classification: A Survey of Deep Learning Techniques, Datasets, and Evaluation Scales
From the last decade, researchers in the field of machine learning (ML) and assistive developmental robotics (ADR) have taken an interest in artificial empathy (AE) as a possible future paradigm for human-robot interaction (HRI).
Indoor Semantic Scene Understanding using Multi-modality Fusion
In this work, we present a semantic scene understanding pipeline that fuses 2D and 3D detection branches to generate a semantic map of the environment.
