Method

RoadFormer+ [RoadFormer+]


Submitted on 22 May. 2024 07:18 by
Rui Fan (Tongji University)

Running time:0.04 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
Please see our paper:
https://arxiv.org/abs/2407.21631
Parameters:
Please see our paper:
https://arxiv.org/abs/2407.21631
Latex Bibtex:
@article{huang2024roadformer+,
title={RoadFormer+: Delivering RGB-X Scene
Parsing through Scale-Aware Information Decoupling
and Advanced Heterogeneous Feature Fusion},
author={Huang, Jianxin and Li, Jiahang and Jia,
Ning and Sun, Yuxiang and Liu, Chengju and Chen,
Qijun and Fan, Rui},
journal={IEEE Transactions on Intelligent
Vehicles},
year={2024}
}

Detailed Results

This page provides detailed results for the method(s) selected. For the first 20 test images, we display the original image, the color-coded result and an error image. The error image contains 4 colors:
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

IoU class iIoU class IoU category iIoU category
73.13 45.88 88.75 73.46
This table as LaTeX

Test Image 0

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Test Image 1

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Test Image 2

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Test Image 3

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Test Image 4

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Test Image 5

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Test Image 6

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Test Image 7

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Test Image 8

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Test Image 9

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