STIT: Spatio-Temporal Interaction Transformers for Human-Object Interaction Recognition in Videos (2022)
Conference Proceeding
Almushyti, M., & Li, F. W. (2022). STIT: Spatio-Temporal Interaction Transformers for Human-Object Interaction Recognition in Videos. . https://doi.org/10.1109/icpr56361.2022.9956030

Recognizing human-object interactions is challenging due to their spatio-temporal changes. We propose the SpatioTemporal Interaction Transformer-based (STIT) network to reason such changes. Specifically, spatial transformers learn humans and objects... Read More about STIT: Spatio-Temporal Interaction Transformers for Human-Object Interaction Recognition in Videos.

Distillation of human–object interaction contexts for action recognition (2022)
Journal Article
Almushyti, M., & Li, F. W. (2022). Distillation of human–object interaction contexts for action recognition. Computer Animation and Virtual Worlds, 33(5), Article e2107. https://doi.org/10.1002/cav.2107

Modeling spatial-temporal relations is imperative for recognizing human actions, especially when a human is interacting with objects, while multiple objects appear around the human differently over time. Most existing action recognition models focus... Read More about Distillation of human–object interaction contexts for action recognition.