World-Consistent Data Generation for Vision-and-Language Navigation

Yu Zhong; Rui Zhang; Zihao Zhang; Shuo Wang; Chuan Fang; Xishan Zhang; Jiaming Guo; Shaohui Peng; Di Huang; Yanyang Yan; Xing Hu; Qi Guo

arXiv · 2412.06413

World-Consistent Data Generation for Vision-and-Language Navigation

Yu Zhong·Rui Zhang·Zihao Zhang·Shuo Wang·Chuan Fang·Xishan Zhang·Jiaming Guo·Shaohui Peng·Di Huang·Yanyang Yan·Xing Hu·Qi Guo

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Abstract

Vision-and-Language Navigation (VLN) is a challenging task that requires an agent to navigate through photorealistic environments following natural-language instructions. One main obstacle existing in VLN is data scarcity, leading to poor generalization performance over unseen environments. Though data argumentation is a promising way for scaling up the dataset, how to generate VLN data both diverse and world-consistent remains problematic. To cope with this issue, we propose the world-consistent data generation (WCGEN), an efficacious data-augmentation framework satisfying both diversity and world-consistency, aimed at enhancing the generalization of agents to novel environments. Roughly, our framework consists of two stages, the trajectory stage which leverages a point-cloud based technique to ensure spatial coherency among viewpoints, and the viewpoint stage which adopts a novel angle synthesis method to guarantee spatial and wraparound consistency within the entire observation. By accurately predicting viewpoint changes with 3D knowledge, our approach maintains the world-consistency during the generation procedure. Experiments on a wide range of datasets verify the effectiveness of our method, demonstrating that our data augmentation strategy enables agents to achieve new state-of-the-art results on all navigation tasks, and is capable of enhancing the VLN agents' generalization ability to unseen environments.

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Yu Zhong, Rui Zhang, Zihao Zhang, Shuo Wang, Chuan Fang, Xishan Zhang, Jiaming Guo, Shaohui Peng, Di Huang, Yanyang Yan, Xing Hu, Qi Guo. 2025-06-25. World-Consistent Data Generation for Vision-and-Language Navigation. https://arxiv.org/abs/2412.06413

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