KITTI-SEMSEG-UNIZG

This is a semantic segmentation dataset collected at University of Zagreb, Faculty of Electrical Engineering and Computing. A more complete dataset description is available at http://www.zemris.fer.hr/~ssegvic/multiclod/kitti_semseg_unizg.shtml This dataset contains groundtruth semantic segmentations for 445 hand-picked images from the KITTI dataset. We start from 146 images annotated by German Ros from UAB Barcelona, improve their annotation accuracy and contribute another 299 images. The annotations feature high quality pixel-level polygonal approximations into 11 semantic classes: building, vegetation, sky, road, fence, pole, sidewalk, sign, car, pedestrian, bicyclist. Dataset was designed by Ivan Krešo and Siniša Šegvić. Images were selected by Ivan Krešo. Annotation was performed by Ivan Borko, Matija Folnović, Petra Marče, Nikola Munđer and Dino Pačandi. The annotation tool was designed by Ivan Fabijanić.此数据集为克罗地亚萨格勒布大学电气与计算机工程学院所收集的语义分割数据集。更详尽的数据集描述可查阅http://www.zemris.fer.hr/~ssegvic/multiclod/kitti_semseg_unizg.shtml。该数据集包含来自KITTI数据集的445幅精心挑选图像的地面真实语义分割。我们起初基于巴塞罗那自治大学UAB的德国Ros标注的146幅图像，提高了其标注的精确度，并额外贡献了299幅图像。标注特征为高质量像素级多边形近似，将11个语义类别：建筑、植被、天空、道路、栅栏、电线杆、人行道、标志、汽车、行人、骑自行车者进行分类。数据集由Ivan Krešo和Siniša Šegvić设计，图像选择由Ivan Krešo负责，标注工作由Ivan Borko、Matija Folnović、Petra Marče、Nikola Munđer和Dino Pačandi完成。标注工具由Ivan Fabijanić设计。

搜集汇总

背景与挑战

背景概述

KITTI-SEMSEG-UNIZG是一个高质量的语义分割数据集，包含445张从KITTI数据集中精选的图像，标注了11个语义类别，适用于计算机视觉研究。