Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas, Mahsa, Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky
{"title":"Supplementary Material","authors":"Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas, Mahsa, Baktashmotlagh, Anders P. Eriksson, Eugene Belilovsky","doi":"10.1002/9781119393382.oth","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":227323,"journal":{"name":"Vibrations of Linear Piezostructures","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vibrations of Linear Piezostructures","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/9781119393382.oth","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.