论文标题
艺术画廊的体现导航
Embodied Navigation at the Art Gallery
论文作者
论文摘要
体现的代理，经过训练，可以探索和浏览室内近现实主义环境，在标准数据集和基准测试方面取得了令人印象深刻的结果。到目前为止，实验和评估涉及家庭和工作场景，例如办公室，公寓和房屋。在本文中，我们构建并发布了一个具有独特特征的新3D空间：完整的艺术博物馆之一。我们将这个环境命名为Artgallery3d（AG3D）。与现有的3D场景相比，收集的空间是放大器，视觉特征更丰富，并且提供了非常稀疏的占用信息。此功能对于基于占用的代理商而言是一项挑战，通常在拥挤的家庭环境中接受大量占用信息的培训。此外，我们注释了博物馆内部关注点的坐标，例如绘画，雕像和其他物品。借助此手动过程，我们在这个新空间内提供了一个新的基准，用于PointGoal导航。该数据集中的轨迹比吉布森和Matterport3D导航的现有地面真相路径要复杂得多。我们使用新的空间进行评估进行广泛的实验评估，并证明现有方法几乎无法适应这种情况。因此，我们认为，这种3D模型的可用性将促进未来的研究，并有助于改善现有解决方案。
Embodied agents, trained to explore and navigate indoor photorealistic environments, have achieved impressive results on standard datasets and benchmarks. So far, experiments and evaluations have involved domestic and working scenes like offices, flats, and houses. In this paper, we build and release a new 3D space with unique characteristics: the one of a complete art museum. We name this environment ArtGallery3D (AG3D). Compared with existing 3D scenes, the collected space is ampler, richer in visual features, and provides very sparse occupancy information. This feature is challenging for occupancy-based agents which are usually trained in crowded domestic environments with plenty of occupancy information. Additionally, we annotate the coordinates of the main points of interest inside the museum, such as paintings, statues, and other items. Thanks to this manual process, we deliver a new benchmark for PointGoal navigation inside this new space. Trajectories in this dataset are far more complex and lengthy than existing ground-truth paths for navigation in Gibson and Matterport3D. We carry on extensive experimental evaluation using our new space for evaluation and prove that existing methods hardly adapt to this scenario. As such, we believe that the availability of this 3D model will foster future research and help improve existing solutions.
