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Found 6 papers, 3 papers with code
A Multilingual Approach to Identify and Classify Exceptional Measures against COVID-19
The COVID-19 pandemic has witnessed the implementations of exceptional measures by governments across the world to counteract its impact.
Language-guided Robot Grasping: CLIP-based Referring Grasp Synthesis in Clutter
To address these limitations, we develop a challenging benchmark based on cluttered indoor scenes from OCID dataset, for which we generate referring expressions and connect them with 4-DoF grasp poses.
Enhancing Fine-Grained 3D Object Recognition using Hybrid Multi-Modal Vision Transformer-CNN Models
Robots operating in human-centered environments, such as retail stores, restaurants, and households, are often required to distinguish between similar objects in different contexts with a high degree of accuracy.
Enhancing Interpretability and Interactivity in Robot Manipulation: A Neurosymbolic Approach
Finally, we integrate our method with a robot framework and demonstrate how it can serve as an interpretable solution for an interactive object-picking task, both in simulation and with a real robot.
Early or Late Fusion Matters: Efficient RGB-D Fusion in Vision Transformers for 3D Object Recognition
We explore which depth representation is better in terms of resulting accuracy and compare early and late fusion techniques for aligning the RGB and depth modalities within the ViT architecture.
Sim-To-Real Transfer of Visual Grounding for Human-Aided Ambiguity Resolution
Service robots should be able to interact naturally with non-expert human users, not only to help them in various tasks but also to receive guidance in order to resolve ambiguities that might be present in the instruction.
