MCubeS Dataset

The MCubeS: Multimodal Material Segmentation Dataset was created it from RGB, polarization, and near-infrared images. Dataset contains 500 sets of multimodal images capturing 42 street scenes. The capacity to discern materials based on their visual attributes is fundamental for computer vision applications, especially those engaged in real-world scenarios. Material segmentation, requiring meticulous identification of materials at a per-pixel level, poses a substantial challenge. Unlike objects, materials lack clear visual signatures in standard RGB representations. Nonetheless, the distinct radiometric behaviors of diverse materials can be aptly captured through alternative imaging modalities beyond RGB. Each image and pixel within the dataset is meticulously annotated with ground truth information for both material segmentation and semantic segmentation.MCubeS：多模态材料分割数据集由RGB、偏振和近红外图像创建而成。该数据集包含500组多模态图像，捕捉了42个街景。基于视觉属性对材料进行辨别的能力对于计算机视觉应用至关重要，尤其是在涉及现实场景的应用中。材料分割，需要精确地识别像素级别的材料，是一项巨大的挑战。与物体不同，材料在标准的RGB表示中缺乏明显的视觉特征。然而，通过RGB以外的其他成像模式，可以恰当地捕捉到不同材料的独特辐射行为。数据集中的每一张图像和每一个像素都经过精心标注，包含材料分割和语义分割的地面真实信息。

搜集汇总

背景与挑战

背景概述

MCubeS数据集是一个用于材料分割的多模态数据集，包含2000张RGB、偏振和近红外图像，涵盖20种材料类别并提供了像素级语义分割标注。该数据集专注于街景场景，旨在通过多模态图像解决材料识别在计算机视觉应用中的挑战，发布于2022年，适用于自动驾驶和建筑行业。