1 citations · 3 across the 5 of their papers we have counts for
6 papers
FenceXR: AR Movement Replay for Error-Detection Training and Spatially Grounded Feedback
Avinash Ajit Nargund, Amelia Haruka Harrison, Timothy Robinson +2
Recognizing technical errors in movement is a perceptual skill important to motor learning, but it is challenging for beginners in fast, complex sports like fencing to develop it.…
How Users Perceive Mixed-Initiative AI: Attitudes Toward Assistance in Problem Solving
Yunhao Luo, Arthur Caetano, Avinash Ajit Nargund +2
In mixed-initiative systems, the mode of AI assistance delivery can be as consequential as the assistance itself. We investigated two assistance delivery modes: on-demand help (use…
Embedded vs. Situated: An Evaluation of AR Facial Training Feedback
Avinash Ajit Nargund, Andrea M. Park, Tobias Höllerer +1
While augmented reality (AR) research demonstrates benefits of embedded visualizations for gross motor training, its applicability to facial exercises remains under-explored. Provi…
Exploration of Radar-based Obstacle Visualizations to Support Safety and Presence in Camera-Free Outdoor VR
Avinash Ajit Nargund, Andrew L. Huard, Tobias Höllerer +1
Outdoor virtual reality (VR) places users in dynamic physical environments where they must remain aware of real-world obstacles, including static structures and moving bystanders,…
Understanding Role Switching in Human-AI Collaboration through Multimodal Behavioral Signals
Avinash Ajit Nargund, Arthur Caetano, Kevin Yang +7
Human-AI collaboration often requires dividing complex tasks into complementary subtasks. As a task unfolds, users may want to shift which subtasks they perform and which their AI…
SPOTR: Spatio-temporal Pose Transformers for Human Motion Prediction
Avinash Ajit Nargund, Misha Sra
3D human motion prediction is a research area of high significance and a challenge in computer vision. It is useful for the design of many applications including robotics and auton…