We present SA-Net a deep neural network architecture that recognizes state-action pairs from RGB-D data streams. SA-Net performs well in two replicated robotic ...

May 31, 2020 · We present SA-Net a deep neural network architecture that recognizes state-action pairs from RGB-D data streams. SA-Net performs well in two ...

SA-Net is presented, a deep neural network architecture that recognizes state-action pairs from RGB-D data streams and significantly improves on the ...

A recent step in this direction is SA-Net (Soans et al. 2020) , which is able to recognize state-action pairs using an RGB-D sensor. However, it still needs to ...

Nov 14, 2023 · MVSA-Net offers a significantly more robust and deployable state-action trajectory generation compared to previous methods.

Sep 28, 2020 · Bibliographic details on SA-Net: Robust State-Action Recognition for Learning from Observations.

Apr 8, 2024 · While several existing computer vision models analyze videos for activity recognition, SA-Net specifically targets robotic LfO from RGB-D data.

Sa-net: Robust state-action recognition for learning from observations. N Soans, E Asali, Y Hong, P Doshi. 2020 IEEE International Conference on Robotics and ...

He developed a deep learning pipeline to recognize state and action ... 2020. "SA-Net: Robust State-Action Recognition for Learning from Observations ...

This work generalizes the SA-Net model to allow the perception of multiple viewpoints of the task activity, integrate them, and better recognize the state ...