{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:17:27Z","timestamp":1740100647041,"version":"3.37.3"},"reference-count":21,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T00:00:00Z","timestamp":1653264000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T00:00:00Z","timestamp":1653264000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,23]]},"DOI":"10.1109\/icassp43922.2022.9746046","type":"proceedings-article","created":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T19:50:34Z","timestamp":1651089034000},"page":"1755-1759","source":"Crossref","is-referenced-by-count":1,"title":["VR-FAM: Variance-Reduced Encoder with Nonlinear Transformation for Facial Attribute Manipulation"],"prefix":"10.1109","author":[{"given":"Yifan","family":"Yuan","sequence":"first","affiliation":[{"name":"Fudan University,School of Computer Science,Shanghai Key Lab of Intelligent Information Processing,Shanghai,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siteng","family":"Ma","sequence":"additional","affiliation":[{"name":"Fudan University,School of Computer Science,Shanghai Key Lab of Intelligent Information Processing,Shanghai,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junping","family":"Zhang","sequence":"additional","affiliation":[{"name":"Fudan University,School of Computer Science,Shanghai Key Lab of Intelligent Information Processing,Shanghai,China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00453"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00232"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.106"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2916751"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00652"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3414685.3417826"},{"key":"ref16","first-page":"3481","article-title":"Which training methods for GANs do actually converge?","author":"mescheder","year":"2018","journal-title":"International Conference on Machine Learning (ICML"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01353"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00482"},{"key":"ref19","article-title":"Progressive growing of GANs for improved quality, stability, and variation","author":"karras","year":"2017","journal-title":"arXiv preprint arXiv 1710 10196"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00813"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00453"},{"key":"ref6","article-title":"GANspace: Discovering interpretable GAN controls","volume":"33","author":"h\u00e4rk\u00f6nen","year":"2020","journal-title":"Advances in Neural IInformation Processing Systems"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3450626.3459838"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00618"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00926"},{"key":"ref2","article-title":"Generative adversarial nets","volume":"27","author":"goodfellow","year":"2014","journal-title":"Advances in Neural IInformation Processing Systems"},{"key":"ref1","article-title":"Auto-encoding variational Bayes","author":"kingma","year":"2013","journal-title":"arXiv preprint arXiv 1312 6114"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01267"},{"key":"ref20","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"arXiv preprint arXiv 1412 6980"},{"key":"ref21","first-page":"6626","article-title":"GANs trained by a two time-scale update rule converge to a local nash equilibrium","author":"heusel","year":"2017","journal-title":"Advances in Neural IInformation Processing Systems"}],"event":{"name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","start":{"date-parts":[[2022,5,23]]},"location":"Singapore, Singapore","end":{"date-parts":[[2022,5,27]]}},"container-title":["ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9745891\/9746004\/09746046.pdf?arnumber=9746046","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,15]],"date-time":"2022-08-15T20:08:56Z","timestamp":1660594136000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9746046\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,23]]},"references-count":21,"URL":"https:\/\/doi.org\/10.1109\/icassp43922.2022.9746046","relation":{},"subject":[],"published":{"date-parts":[[2022,5,23]]}}}