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Hyperspectral City V1.0 Dataset and Benchmark

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arxiv 1907.10270 v4 pith:LO6V77OI submitted 2019-07-24 cs.CV

Shaodi You , Erqi Huang , Shuaizhe Liang , Yongrong Zheng , Yunxiang Li , Fan Wang , Sen Lin , Qiu Shen
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Xun Cao Diming Zhang Yuanjiang Li Yu Li Ying Fu Boxin Shi Feng Lu Yinqiang Zheng Robby T. Tan
This is my paper · ORCID
classification cs.CV
keywords datasetcityhyperspectralbackgroundbenchmarkmethodusagebriefly
verification ladder T0 review T1 audit T2 compute T3 formal

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This document introduces the background and the usage of the Hyperspectral City Dataset and the benchmark. The documentation first starts with the background and motivation of the dataset. Follow it, we briefly describe the method of collecting the dataset and the processing method from raw dataset to the final release dataset, specifically, the version 1.0. We also provide the detailed usage of the dataset and the evaluation metric for submitted the result for the 2019 Hyperspectral City Challenge.

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Cited by 2 Pith papers

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    cs.CV 2025-07 conditional novelty 6.0 of 10

    An iterative pruning plus quantization co-design compresses a U-Net for hyperspectral driving-scene segmentation to 1% of its parameters, enabling a 2.86x inference speed-up on an FPGA SoC with negligible accuracy loss.

  2. HSI-Drive v2.0: More Data for New Challenges in Scene Understanding for Autonomous Driving

    cs.CV 2024-11 conditional novelty 4.0 of 10

    HSI-Drive v2.0 nearly triples the size of a hyperspectral driving dataset and reports improved segmentation for roads, vegetation, painted metal, and pedestrians across seasonal conditions.

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