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Continual Vision-and-Language Navigation
March 25, 2024, 4:44 a.m. | Seongjun Jeong, Gi-Cheon Kang, Seongho Choi, Joochan Kim, Byoung-Tak Zhang
cs.CV updates on arXiv.org arxiv.org
Abstract: Vision-and-Language Navigation (VLN) agents navigate to a destination using natural language instructions and the visual information they observe. Existing methods for training VLN agents presuppose fixed datasets, leading to a significant limitation: the introduction of new environments necessitates retraining with previously encountered environments to preserve their knowledge. This makes it difficult to train VLN agents that operate in the ever-changing real world. To address this limitation, we present the Continual Vision-and-Language Navigation (CVLN) paradigm, designed …
abstract agents arxiv continual cs.ai cs.cv datasets environments information introduction knowledge language natural natural language navigation observe retraining training type vision vision-and-language visual
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