2 citations · 2 across the 5 of their papers we have counts for
5 papers
Fiber Optic Sensing Glove for High Performance Dexterous Manipulation Capture
J. D. Peiffer, Taylor Niehues, Li Guan +2
Capturing hand pose during dexterous manipulation remains difficult: vision-based methods degrade under occlusion and challenging lighting, while sensorized gloves, though occlusio…
Pose-Aware Modeling to Mitigate Pose-Related Artifacts in Tactile Gloves
Tianhong Catherine Yu, Ziyi Kou, Mia Huang +4
Tactile gloves digitize contact and force during hand-object interactions, enabling robotics applications in dexterous manipulation, teleoperation, and learning from demonstration.…
Glove2Hand: Synthesizing Natural Hand-Object Interaction from Multi-Modal Sensing Gloves
Xinyu Zhang, Ziyi Kou, Chuan Qin +7
Understanding hand-object interaction (HOI) is fundamental to computer vision, robotics, and AR/VR. However, conventional hand videos often lack essential physical information such…
AirGlove: Exploring Egocentric 3D Hand Tracking and Appearance Generalization for Sensing Gloves
Wenhui Cui, Ziyi Kou, Chuan Qin +2
Sensing gloves have become important tools for teleoperation and robotic policy learning as they are able to provide rich signals like speed, acceleration and tactile feedback. A c…
Glissando-Net: Deep sinGLe vIew category level poSe eStimation ANd 3D recOnstruction
Bo Sun, Hao Kang, Li Guan +3
We present a deep learning model, dubbed Glissando-Net, to simultaneously estimate the pose and reconstruct the 3D shape of objects at the category level from a single RGB image. P…