Semantically-aware spatio-temporal reasoning agent for vision-and-language navigation in continuous environments
This paper presents a novel approach for the Vision-and-Language Navigation (VLN) task in
continuous 3D environments, which requires an autonomous agent to follow natural
language instructions in unseen environments. Existing end-to-end learning-based VLN
methods struggle at this task as they focus mostly on utilizing raw visual observations and
lack the semantic spatio-temporal reasoning capabilities which is crucial in generalizing to
new environments. In this regard, we present a hybrid transformer-recurrence model which …
continuous 3D environments, which requires an autonomous agent to follow natural
language instructions in unseen environments. Existing end-to-end learning-based VLN
methods struggle at this task as they focus mostly on utilizing raw visual observations and
lack the semantic spatio-temporal reasoning capabilities which is crucial in generalizing to
new environments. In this regard, we present a hybrid transformer-recurrence model which …
SASRA: Semantically-aware Spatio-temporal Reasoning Agent for Vision-and-Language Navigation in Continuous Environments
M Zubair Irshad, N Chowdhury Mithun… - arXiv e …, 2021 - ui.adsabs.harvard.edu
This paper presents a novel approach for the Vision-and-Language Navigation (VLN) task in
continuous 3D environments, which requires an autonomous agent to follow natural
language instructions in unseen environments. Existing end-to-end learning-based VLN
methods struggle at this task as they focus mostly on utilizing raw visual observations and
lack the semantic spatio-temporal reasoning capabilities which is crucial in generalizing to
new environments. In this regard, we present a hybrid transformer-recurrence model which …
continuous 3D environments, which requires an autonomous agent to follow natural
language instructions in unseen environments. Existing end-to-end learning-based VLN
methods struggle at this task as they focus mostly on utilizing raw visual observations and
lack the semantic spatio-temporal reasoning capabilities which is crucial in generalizing to
new environments. In this regard, we present a hybrid transformer-recurrence model which …
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