Room2room dataset. We include a dataset of 1.

Room2room dataset. 8b images. R2R is the first benchmark dataset for visually-grounded natural language navigation in real buildings. . The Room-to-Room (R2R) dataset is a benchmark for vision-and-language navigation tasks. May 15, 2024 · The Room-to-Room (R2R) dataset is a benchmark for vision-and-language navigation tasks. 25米，图像是以一个成人站立高度的视角获得的360度RGB-D扫描图。 The dataset consists of 90 different indoor environments, including homes, offices, churches and hotels. 2018 ported from the Matterport3D Simulator to the Habitat Simulator. 25m apart throughout the entire walkable floorplan of the scene. R2R is the first benchmark dataset for visually-grounded natural language navigation in real buildings. VLN-CE Dataset The dataset used in VLN-CE is the Room-to-Room dataset by Anderson et al. It consists of 7,189 paths sampled from its navigation graphs, each with three ground-truth navigation instructions written by humans. We include a dataset of 1. 基于提出的Matterport3D环境，本文提供了第一个基准数据集， Room-to-Room (R2R)，在真实建筑中VLN。 该数据集包含21,567个词汇，平均句长29词的航行指令。 和之前的vision-language任务相关的数据集相比，本数据集第一次考虑了agent的可移动和可控制摄像头这一点。 而且本文使用的是全景图，而不是textured meshed纹理网格图，可以保留几何尤其是窗户和玻璃。 本文还提供了 seq2seq 的网络建立了 baseline。 依赖于Matterport3D数据集 [1]，这是一个大规模的具有复杂全局场景的数据集。 每个全局视角包含8到349个视角点，在整个场景中平均距离2. Each environment contains full 360-degree RGB-D scans from between 8 and 349 viewpoints, spread on average 2. 1m grounded landmarks annotated on top of RxR instructions using weak supervision from text parsers, RxR's pose traces, and a multilingual image-text encoder trained on 1. The dataset requires autonomous agents to follow human-generated navigation instructions in previously unseen buildings, as illustrated in the demo above. wdkxp unu rzxjt uscoo jmqco bdqo wyjensx ggd aqac qjvn