IMNearth/Curriculum-Learning-For-VLN
Code for NeurIPS 2021 paper "Curriculum Learning for Vision-and-Language Navigation"
This project offers code to help researchers and developers in the field of AI create or improve agents that can navigate virtual environments. It takes image features and textual instructions as input and outputs a trained navigation model capable of understanding and executing complex routes. This is primarily for AI researchers and machine learning engineers working on embodied AI, robotics, or natural language understanding in simulated spaces.
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Use this if you are developing or studying AI agents that need to interpret natural language instructions to navigate 3D environments, especially if you are interested in curriculum learning techniques to improve their training efficiency and performance.
Not ideal if you are looking for a plug-and-play solution for a real-world robotics application or if you don't have experience with deep learning frameworks like PyTorch and setting up simulation environments.
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Python
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MIT
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Last pushed
Dec 13, 2022
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