Multi-View Labelling (MVL) Dataset

To overcome the shortage of real-world multi-view multiple people, we introduce a new synthetic multi-view multiple people labelling dataset named Multi-View 3D Humans (MV3DHumans). This dataset is a large-scale synthetic image dataset that was generated for multi-view multiple people detection, labelling and segmentation tasks. The MV3DHumans dataset contains 1200 scenes captured by multiple cameras, with 4, 6, 8 or 10 people in each scene. Each scene is captured by 16 cameras with overlapping field of views. The MV3DHumans dataset provides RGB images with resolution of 640 × 480. Ground truth annotations including bounding boxes, instance masks and multi-view correspondences, as well as camera calibrations are provided in the dataset.

为解决真实世界多视角多人场景数据匮乏的问题，我们推出一款新型合成多视角多人标注数据集——多视角3D人体数据集（Multi-View 3D Humans，简称MV3DHumans）。该数据集为大规模合成图像数据集，专为多视角多人检测、标注与分割任务设计。MV3DHumans数据集共包含1200组由多相机采集的场景，每个场景内包含4、6、8或10位人物；每个场景均由16台视场重叠的相机完成采集。数据集提供分辨率为640×480的RGB图像，同时附带真值标注，涵盖边界框、实例掩码与多视角对应关系，此外还提供相机标定参数。

搜集汇总

背景与挑战

背景概述

Multi-View Labelling (MVL) Dataset是一个大规模合成图像数据集，名为Multi-View 3D Humans (MV3DHumans)，专为多视角多人检测、标注和分割任务设计。数据集包含1200个场景，每个场景由16个重叠视场的摄像头拍摄，每场景有4至10人，提供640×480分辨率的RGB图像以及边界框、实例掩码、多视角对应关系和相机校准的真实标注。