KITTI-360

Method

Pyramid Scene Parsing Network [PSPNet]
https://github.com/hszhao/semseg

Submitted on 21 Oct. 2021 13:18 by
Yiyi Liao (MPI)

Running time:0.2 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
CVPR 2017. Trained and evaluated by KITTI-360 authors.
Parameters:
none
Latex Bibtex:
@InProceedings{Zhao2017CVPR,
author = {Hengshuang Zhao and Jianping Shi
and Xiaojuan Qi and Xiaogang Wang and Jiaya Jia},
title = {Pyramid Scene Parsing Network},
booktitle = {CVPR},
year = {2017},
}

Detailed Results

This page provides detailed results for the method(s) selected. For the first 10 test images, we display the original image, the color-coded result and an error image. The error image contains 4 colors weighted by the confidence of the pseudo-ground truth:
red: the pixel has the wrong label and the wrong category
yellow: the pixel has the wrong label but the correct category
green: the pixel has the correct label
black: the groundtruth label is not used for evaluation

Test Set Average

road sidewalk building wall fence pole traffic light traffic sign vegetation terrain sky person rider car truck motorcycle bicycle mIoU class
96.60 87.34 87.02 65.00 55.61 40.07 0.00 43.04 92.56 88.41 91.93 55.51 48.30 95.59 60.38 52.07 44.12 64.92
flat construction object nature human vehicle sky mIoU category
96.93 86.91 44.22 93.56 66.08 95.56 91.93 82.17
This table as LaTeX

Test Image 0

Input Image

Prediction

Error


Test Image 1

Input Image

Prediction

Error


Test Image 2

Input Image

Prediction

Error


Test Image 3

Input Image

Prediction

Error


Test Image 4

Input Image

Prediction

Error


Test Image 5

Input Image

Prediction

Error


Test Image 6

Input Image

Prediction

Error


Test Image 7

Input Image

Prediction

Error


Test Image 8

Input Image

Prediction

Error


Test Image 9

Input Image

Prediction

Error





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