1 citations · 1 across the 2 of their papers we have counts for
5 papers
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Open-H-Embodiment Consortium, :, Nigel Nelson +213
Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medic…
Encoder-Free Human Motion Understanding via Structured Motion Descriptions
Yao Zhang, Zhuchenyang Liu, Thomas Ploetz +1
The world knowledge and reasoning capabilities of text-based large language models (LLMs) are advancing rapidly, yet current approaches to human motion understanding, including mot…
Hierarchical Motion Captioning Utilizing External Text Data Source
Clayton Leite, Yu Xiao
This paper introduces a novel approach to enhance existing motion captioning methods, which directly map representations of movement to high-level descriptive captions (e.g., ``a p…
Transformer-Based Approaches for Sensor-Based Human Activity Recognition: Opportunities and Challenges
Clayton Souza Leite, Henry Mauranen, Aziza Zhanabatyrova +1
Transformers have excelled in natural language processing and computer vision, paving their way to sensor-based Human Activity Recognition (HAR). Previous studies show that transfo…
Enhancing Motion Variation in Text-to-Motion Models via Pose and Video Conditioned Editing
Clayton Leite, Yu Xiao
Text-to-motion models that generate sequences of human poses from textual descriptions are garnering significant attention. However, due to data scarcity, the range of motions thes…