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Outputs (5)

NeFT-Net: N-window Extended Frequency Transformer for Rhythmic Motion Prediction (2025)
Journal Article
Ademola, A., Sinclair, D., Koniaris, B., Hannah, S., & Mitchell, K. (in press). NeFT-Net: N-window Extended Frequency Transformer for Rhythmic Motion Prediction. Computers and Graphics,

Advancements in prediction of human motion sequences are critical for enabling online virtual reality (VR) users to dance and move in ways that accurately mirror real-world actions, delivering a more immersive and connected experience. However, laten... Read More about NeFT-Net: N-window Extended Frequency Transformer for Rhythmic Motion Prediction.

DeFT-Net: Dual-Window Extended Frequency Transformer for Rhythmic Motion Prediction (2024)
Presentation / Conference Contribution
Ademola, A., Sinclair, D., Koniaris, B., Hannah, S., & Mitchell, K. (2024, September). DeFT-Net: Dual-Window Extended Frequency Transformer for Rhythmic Motion Prediction. Presented at EG UK Computer Graphics & Visual Computing (2024), London, UK

Enabling online virtual reality (VR) users to dance and move in a way that mirrors the real-world necessitates improvements in the accuracy of predicting human motion sequences paving way for an immersive and connected experience. However, the drawba... Read More about DeFT-Net: Dual-Window Extended Frequency Transformer for Rhythmic Motion Prediction.

DanceMark: An open telemetry framework for latency sensitive real-time networked immersive experiences (2024)
Presentation / Conference Contribution
Koniaris, B., Sinclair, D., & Mitchell, K. (2024, March). DanceMark: An open telemetry framework for latency sensitive real-time networked immersive experiences. Presented at IEEE VR Workshop on Open Access Tools and Libraries for Virtual Reality, Orlando, FL

DanceMark is an open telemetry framework designed for latency-sensitive real-time networked immersive experiences, focusing on online dancing in virtual reality within the DanceGraph platform. The goal is to minimize end-to-end latency and enhance us... Read More about DanceMark: An open telemetry framework for latency sensitive real-time networked immersive experiences.

Design Considerations of Voice Articulated Generative AI Virtual Reality Dance Environments (2024)
Presentation / Conference Contribution
Casas, L., Mitchell, K., Tamariz, M., Hannah, S., Sinclair, D., Koniaris, B., & Kennedy, J. (2024, May). Design Considerations of Voice Articulated Generative AI Virtual Reality Dance Environments. Presented at SIGCHI GenAI in UGC Workshop, Honolulu, Hawaii

We consider practical and social considerations of collaborating verbally with colleagues and friends, not confined by physical distance, but through seamless networked telepresence to interactively create shared virtual dance environments. In respon... Read More about Design Considerations of Voice Articulated Generative AI Virtual Reality Dance Environments.