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Found 5 papers, 2 papers with code
Fusing Hand and Body Skeletons for Human Action Recognition in Assembly
As collaborative robots (cobots) continue to gain popularity in industrial manufacturing, effective human-robot collaboration becomes crucial.
How Object Information Improves Skeleton-based Human Action Recognition in Assembly Tasks
Our research sheds light on the benefits of combining skeleton joints with object information for human action recognition in assembly tasks.
Efficient Multi-Task RGB-D Scene Analysis for Indoor Environments
In order to evaluate our multi-task approach, we extend the annotations of the common RGB-D indoor datasets NYUv2 and SUNRGB-D for instance segmentation and orientation estimation.
Few-Shot Object Detection: A Comprehensive Survey
To avoid the need to acquire and annotate these huge amounts of data, few-shot object detection aims to learn from few object instances of new categories in the target domain.
Efficient RGB-D Semantic Segmentation for Indoor Scene Analysis
In this paper, we propose an efficient and robust RGB-D segmentation approach that can be optimized to a high degree using NVIDIA TensorRT and, thus, is well suited as a common initial processing step in a complex system for scene analysis on mobile robots.
