Short Term Object Interaction Anticipation

Short-term object interaction anticipation (STA) focuses on predicting upcoming human-object interactions within egocentric videos, including the interacting objects, the type of interaction, and the timing. Current research emphasizes the use of attention-based transformer networks, often incorporating affordance modeling and multi-modal fusion techniques to improve prediction accuracy. These advancements are crucial for developing more intuitive and responsive human-computer interaction systems, particularly in applications like wearable assistants and human-robot collaboration, by enabling proactive and context-aware responses. The field is actively developing robust benchmarks and datasets to facilitate further progress.