Shapenet Illuminants - dataset from "Zero-Shot Day-Night Domain Adaptation with a Physics Prior"

Shapenet Illuminants is the synthetic classification dataset used in the ICCV '21 publication "Zero-Shot Day-Night Domain Adaptation with a Physics Prior". The images have been rendered from the ShapeNet dataset using the Mitsuba rendering engine. See the readme for more information on using the dataset. ArXiv: https://arxiv.org/abs/2108.05137Code: https://github.com/Attila94/CIConv If you find this dataset useful, please cite:@article{lengyel2021zeroshot, title={Zero-Shot Domain Adaptation with a Physics Prior}, author={Attila Lengyel and Sourav Garg and Michael Milford and Jan C. van Gemert}, year={2021}, eprint={2108.05137}, archivePrefix={arXiv}, primaryClass={cs.CV}}

形状网络光照数据集（Shapenet Illuminants）是发表于国际计算机视觉大会（ICCV）2021年会论文《基于物理先验的零样本昼夜域自适应（Zero-Shot Day-Night Domain Adaptation with a Physics Prior）》中所用的合成分类数据集。该数据集的图像均通过Mitsuba渲染引擎，基于形状网络（ShapeNet）数据集渲染生成。有关该数据集的使用详情，请参阅其自述文件（README）。论文预印本链接：https://arxiv.org/abs/2108.05137；代码仓库地址：https://github.com/Attila94/CIConv。若您认为本数据集对研究工作有所助益，请引用如下文献：@article{lengyel2021zeroshot, title={基于物理先验的零样本昼夜域自适应}, author={Attila Lengyel and Sourav Garg and Michael Milford and Jan C. van Gemert}, year={2021}, eprint={2108.05137}, archivePrefix={arXiv}, primaryClass={cs.CV}}