Generative AI (GenAI) has significantly advanced the ease and flexibility of image creation. However, it remains a challenge to precisely control spatial compositions, including object arrangement and scene conditions. To bridge this gap, we...
Large language models (LLMs) are capable of generating cross-domain design knowledge, opening up new possibilities for creating a myriad of design concepts for early-stage design ideation. However, the current chat-based interface fails to...
Creating Augmented Reality (AR) applications requires expertise in both design and implementation, posing significant barriers to entry for non-expert users. While existing methods reduce some of this burden, they often fall short in flexibility or...
Extended Reality (XR)-enabled headsets that overlay digital content onto the physical world, are gradually finding their way into our daily life. This integration raises significant concerns about privacy and access control, especially in shared...
Context-aware AR instruction enables adaptive and in-situ learning experiences. However, hardware limitations and expertise requirements constrain the creation of such instructions. With recent developments in Generative Artificial Intelligence...
Mixed Reality (MR) is gaining prominence in manual task skill learning due to its in-situ, embodied, and immersive experience. To teach manual tasks, current methodologies break the task into hierarchies (tasks into subtasks) and visualize not only...
Table tennis stroke training is a critical aspect of player development. We designed a new augmented reality (AR) system, avaTTAR, for table tennis stroke training. The system provides both "on-body" (first-person view) and "detached" (third-person...
Interacting Objects: A dataset of object-object interactions for richer dynamic scene representations Asim Unmesh, Rahul Jain, Jingyu Shi, V. K. Chaithanya Manam, Hyung-Gun Chi, Subramanian Chidambaram, Alexander J. Quinn, Karthik Ramani IEEE...