date: 2020-01-31T14:38:33Z pdf:unmappedUnicodeCharsPerPage: 0 pdf:PDFVersion: 1.3 pdf:docinfo:title: IsMo-GAN: Adversarial Learning for Monocular Non-Rigid 3D Reconstruction dc:description: IEEE Conference on Computer Vision and Pattern Recognition Workshops access_permission:modify_annotations: true access_permission:can_print_degraded: true subject: IEEE Conference on Computer Vision and Pattern Recognition Workshops dc:creator: Soshi Shimada description: IEEE Conference on Computer Vision and Pattern Recognition Workshops Last-Modified: 2020-01-31T14:38:33Z dcterms:modified: 2020-01-31T14:38:33Z dc:format: application/pdf; version=1.3 title: IsMo-GAN: Adversarial Learning for Monocular Non-Rigid 3D Reconstruction xmpMM:DocumentID: uuid:626f6c3c-0f10-4b15-aa7e-977e931a3aa8 Last-Save-Date: 2020-01-31T14:38:33Z access_permission:fill_in_form: true pdf:docinfo:modified: 2020-01-31T14:38:33Z meta:save-date: 2020-01-31T14:38:33Z pdf:encrypted: false dc:title: IsMo-GAN: Adversarial Learning for Monocular Non-Rigid 3D Reconstruction modified: 2020-01-31T14:38:33Z cp:subject: IEEE Conference on Computer Vision and Pattern Recognition Workshops pdf:docinfo:subject: IEEE Conference on Computer Vision and Pattern Recognition Workshops Content-Type: application/pdf pdf:docinfo:creator: Soshi Shimada, Vladislav Golyanik, Christian Theobalt, Didier Stricker X-Parsed-By: org.apache.tika.parser.DefaultParser creator: Soshi Shimada meta:author: Soshi Shimada access_permission:extract_for_accessibility: true access_permission:assemble_document: true xmpTPg:NPages: 10 pdf:charsPerPage: 3037 access_permission:extract_content: true access_permission:can_print: true Author: Soshi Shimada producer: PyPDF2 access_permission:can_modify: true pdf:docinfo:producer: PyPDF2