This archive contains full versions of the datasets and additional data presented in the following paper: A Priority Map for Vision-and-Language Navigation with Trajectory Plans and Feature-Location Cues A priority map module (PM-VLN) boosts the performance of transformer-based architectures in navigation tasks by combining temporal sequence alignment and feature-level localisation in cross-modal inputs. The module is pretrained on trajectory estimation and a multi-objective task that pairs location estimation with cross-modal sentence prediction. Two datasets are introduced for the auxiliary tasks: - TR-NY-PIT-central - a set of path traces for routes in two urban locations. - MC-10 - a set of samples with multimodal inputs representing landmarks in 10 US cities. Full details and links for this research are available at the following link: https://jasonarmitage-res.github.io/projects/priority_map/ Additional data comprising path traces for routes in Manhattan and language tokens for the Touchdown task are provided for training and evaluating the PM-VLN and framework on the Touchdown benchmark. Please refer to the following link for details on the Touchdown dataset and StreetLearn environment: https://sites.google.com/view/streetlearn/touchdown

This research is supported by the Digital Visual Studies program at the University of Zurich and funded by the Max Planck Society.