补充材料

Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas, Mahsa, Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky
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引用次数: 0

摘要

我们提供额外的材料来补充我们的工作。附录A验证了我们重新实现[1]的准确性,据我们所知,这是之前唯一的几次3D重建工作。附录B进一步研究了将形状先验合并到[1]的编码器-解码器架构中的方法。在附录C中,我们报告了我们所考虑的三种方法和Wallace等人的基类性能[1]。附录D显示了使用CGCE模型获得的学习注意图,分析了不同类别的相似性以及超参数的选择。最后,我们在附录E中提供了更多定性的例子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Supplementary Material
We provide additional material to supplement our work. Appendix A verifies the accuracy of our re-implementation of [1], which is, to our knowledge, the only pre-existing work on few-shot 3D reconstruction. Appendix B further examines ways of incorporating shape priors into the encoder-decoder architecture of [1]. In Appendix C, we report performance on base classes for our three considered methods and Wallace et al. [1]. Appendix D shows learned attention maps obtained using the CGCE model, analyses similarities across classes, and the choice of hyperparameters. Finally, we provide more qualitative examples in Appendix E.
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