论文

本文提出 DashboardQA，这是首个明确设计用于评估视觉-语言 GUI Agent 对真实世界仪表板理解与交互能力的基准，结果表明交互式仪表板推理对所有受评估的 VLM 而言都是一项具有挑战性的任务。DashboardQA is introduced, the first benchmark explicitly designed to assess how vision-language GUI agents comprehend and interact with real-world dashboards, and indicates that interactive dashboard reasoning is a challenging task overall for all the VLMs evaluated.

本文推出 ScanNet，一个 RGB-D 视频数据集，包含 1513 个场景中的 250 万视角，标注有三维相机位姿、表面重建与语义分割，并表明使用该数据可在多项三维场景理解任务上取得 SOTA 性能。This work introduces ScanNet, an RGB-D video dataset containing 2.5M views in 1513 scenes annotated with 3D camera poses, surface reconstructions, and semantic segmentations, and shows that using this data helps achieve state-of-the-art performance on several 3D scene understanding tasks.

本文介绍 Matterport3D，一个大规模 RGB-D 数据集，包含来自 90 个建筑物级场景共 194,400 张 RGB-D 图像的 10,800 个全景视图，可支持多种监督与自监督计算机视觉任务，包括关键点匹配、视角重叠预测、由彩色图像预测法线、语义分割和区域分类。Matterport3D is introduced, a large-scale RGB-D dataset containing 10,800 panoramic views from 194,400RGB-D images of 90 building-scale scenes that enable a variety of supervised and self-supervised computer vision tasks, including keypoint matching, view overlap prediction, normal prediction from color, semantic segmentation, and region classification.