{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T07:42:58Z","timestamp":1763192578380,"version":"3.45.0"},"reference-count":54,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,6,30]]},"DOI":"10.1109\/ijcnn64981.2025.11227957","type":"proceedings-article","created":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T18:46:15Z","timestamp":1763145975000},"page":"1-8","source":"Crossref","is-referenced-by-count":0,"title":["Dynamic Generative Adaptation for Data-Efficient GAN"],"prefix":"10.1109","author":[{"given":"Divya","family":"Saxena","sequence":"first","affiliation":[{"name":"The Hong Kong Polytechnic University,Department of Computing,Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiannong","family":"Cao","sequence":"additional","affiliation":[{"name":"The Hong Kong Polytechnic University,Department of Computing,Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tarun","family":"Kulshrestha","sequence":"additional","affiliation":[{"name":"The Hong Kong Polytechnic University,UBDA,Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuqing","family":"Zhao","sequence":"additional","affiliation":[{"name":"The Hong Kong Polytechnic University,Department of Computing,Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.5555\/2969033.2969125"},{"key":"ref2","first-page":"12104","article-title":"Training generative adversarial networks with limited data","author":"Karras","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3446374"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01039"},{"key":"ref5","first-page":"7921","article-title":"Improving 3d-aware image synthesis with a geometry-aware discriminator","volume":"35","author":"Shi","year":"2022","journal-title":"Adv Neural Inf Process Syst"},{"key":"ref6","first-page":"9378","article-title":"Data-efficient instance generation from instance discrimination","volume":"34","author":"Yang","year":"2021","journal-title":"Adv Neural Inf Process Syst"},{"article-title":"The relativistic discriminator: a key element missing from standard gan","volume-title":"International Conference on Learning Representations","author":"Jolicoeur-Martineau","key":"ref7"},{"key":"ref8","first-page":"7559","article-title":"Differentiable augmentation for data-efficient gan training","author":"Zhao","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref9","first-page":"21655","article-title":"Deceive d: adaptive pseudo augmentation for gan training with limited data","author":"Jiang","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01557"},{"key":"ref11","first-page":"15093","article-title":"Improving gans with a dynamic discriminator","volume":"30","author":"Yang","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00813"},{"article-title":"Large scale gan training for high fidelity natural image synthesis","volume-title":"Proceedings of International Conference on Learning Representations, ICLR 2019","author":"Brock","key":"ref13"},{"article-title":"Progressive growing of gans for improved quality, stability, and variation","volume-title":"6th International Conference on Learning Representations, ICLR","author":"Karras","key":"ref14"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00453"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.425"},{"key":"ref17","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-70139-4","article-title":"Unsupervised image-to-image translation networks","volume":"30","author":"Liu","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00821"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58595-2_43"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00282"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/WACV61041.2025.00719"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00308"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3115428"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00905"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19790-1_25"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1802.05957"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2970919"},{"key":"ref30","first-page":"2154","article-title":"Masked generative adversarial networks are data-efficient generation learners","volume-title":"NeurIPS","volume":"35","author":"Huang"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19784-0_35"},{"key":"ref32","article-title":"Augmentation-aware self-supervision for data-efficient gan training","volume-title":"NeurIPS","volume":"36","author":"Hou"},{"key":"ref33","first-page":"20941","article-title":"Data-efficient gan training beyond (just) augmentations: A lottery ticket perspective","author":"Chen","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref34","first-page":"9378","article-title":"Data-efficient instance generation from instance discrimination","volume-title":"NeurIPS","volume":"34","author":"Yang"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00377"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01231-1_14"},{"article-title":"Deep generative modeling on limited data with regularization by nontransferable pre-trained models","volume-title":"ICLR","author":"Zhong","key":"ref37"},{"key":"ref38","first-page":"10743","article-title":"Fewshot image generation via cross-domain correspondence","volume-title":"CVPR","author":"Ojha"},{"article-title":"Consistency regularization for generative adversarial networks","volume-title":"ICLR","author":"Zhang","key":"ref39"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3226416"},{"article-title":"The role of imagenet classes in frechet inception distance","volume-title":"ICLR","author":"Kynkaanniemi","key":"ref41"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2019.2897874"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00783"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i1.19928"},{"key":"ref45","first-page":"31782","article-title":"Diggan: Discriminator gradient gap regularization for gan training with limited data","volume-title":"NeurIPS","volume":"35","author":"Fang"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00646"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i5.28271"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00888"},{"article-title":"Message passing multi-agent gans","year":"2016","author":"Ghosh","key":"ref49"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.3156\/jsoft.29.5_177_2"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_8"},{"key":"ref52","article-title":"Gans trained by a two time-scale update rule converge to a local nash equilibrium","volume":"30","author":"Heusel","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"article-title":"Towards faster and stabilized gan training for high-fidelity few-shot image synthesis","volume-title":"International Conference on Learning Representations","author":"Liu","key":"ref53"},{"key":"ref54","first-page":"214","article-title":"Wasserstein generative adversarial networks","volume-title":"International Conference on Machine Learning","author":"Arjovsky"}],"event":{"name":"2025 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2025,6,30]]},"location":"Rome, Italy","end":{"date-parts":[[2025,7,5]]}},"container-title":["2025 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11227166\/11227148\/11227957.pdf?arnumber=11227957","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T07:38:50Z","timestamp":1763192330000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11227957\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":54,"URL":"https:\/\/doi.org\/10.1109\/ijcnn64981.2025.11227957","relation":{},"subject":[],"published":{"date-parts":[[2025,6,30]]}}}