{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T10:05:19Z","timestamp":1777889119315,"version":"3.51.4"},"reference-count":49,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"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":[[2025,10,19]]},"DOI":"10.1109\/iccv51701.2025.00459","type":"proceedings-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T19:45:49Z","timestamp":1777491949000},"page":"4828-4837","source":"Crossref","is-referenced-by-count":0,"title":["LIFT: Latent Implicit Functions for Task- and Data-Agnostic Encoding"],"prefix":"10.1109","author":[{"given":"Amirhossein","family":"Kazerouni","sequence":"first","affiliation":[{"name":"University of Toronto, Vector Institute, University Health Network"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Soroush","family":"Mehraban","sequence":"additional","affiliation":[{"name":"University of Toronto, Vector Institute, University Health Network"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Brudno","sequence":"additional","affiliation":[{"name":"University of Toronto, Vector Institute, University Health Network"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Babak","family":"Taati","sequence":"additional","affiliation":[{"name":"University of Toronto, Vector Institute, University Health Network"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Spatial functa: Scaling functa to imagenet classification and generation","author":"Bauer","year":"2023","journal-title":"arXiv preprint"},{"key":"ref2","author":"Bradbury","year":"2018","journal-title":"JAX: composable transformations of Python+ NumPy programs"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00574"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01565"},{"key":"ref5","article-title":"Shapenet: An information-rich 3d model repository","author":"Chang","year":"2015","journal-title":"arXiv preprint"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72933-1_23"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00852"},{"key":"ref8","article-title":"An image is worth $16 \\times 16$ words: Transformers for image recognition at scale","author":"Dosovitskiy","journal-title":"arXiv preprint"},{"key":"ref9","first-page":"8320","article-title":"Learning signal-agnostic manifolds of neural fields","volume":"34","author":"Du","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref10","first-page":"5694","article-title":"From data to functa: Your data point is a function and you can treat it like one","volume-title":"International Conference on Machine Learning","author":"Dupont"},{"key":"ref11","first-page":"2989","article-title":"Generative models as distributions of functions","volume-title":"International Conference on Artificial Intelligence and Statistics","author":"Dupont"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01315"},{"key":"ref13","article-title":"Multiplicative filter networks","volume-title":"International Conference on Learning Representations","author":"Fathony","year":"2020"},{"key":"ref14","article-title":"Hypernetworks","volume-title":"International Conference on Learning Representations","author":"Ha","year":"2017"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref16","author":"Hennigan","year":"2020","journal-title":"Haiku: Sonnet for JAX"},{"key":"ref17","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"},{"key":"ref18","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume":"33","author":"Ho","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref19","article-title":"Progressive growing of gans for improved quality, stability, and variation","author":"Karras","year":"2017","journal-title":"arXiv preprint"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00133"},{"key":"ref21","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"arXiv preprint"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-30493-5_48"},{"issue":"4","key":"ref23","first-page":"1","volume":"5","author":"Krizhevsky","year":"2010","journal-title":"Cifar-10 (canadian institute for advanced research)"},{"key":"ref24","article-title":"Vmamba: Visual state space model","author":"Liu","year":"2024","journal-title":"arXiv preprint"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01170"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72633-0_16"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01395"},{"key":"ref28","first-page":"7176","article-title":"Reliable fidelity and diversity metrics for generative models","volume-title":"International Conference on Machine Learning","author":"Naeem"},{"key":"ref29","article-title":"DDMI: Domain-agnostic latent diffusion models for synthesizing high-quality implicit neural representations","volume-title":"The Twelfth International Conference on Learning Representations","author":"Park","year":"2024"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00025"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11671"},{"key":"ref32","first-page":"5301","article-title":"On the spectral bias of neural networks","volume-title":"International conference on machine learning","author":"Rahaman"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19827-4_9"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref35","article-title":"Assessing generative models via precision and recall","volume":"31","author":"Sajjadi","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01775"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2006.09661"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01061"},{"key":"ref39","article-title":"Denoising diffusion implicit models","volume-title":"International Conference on Learning Representations","author":"Song","year":"2021"},{"key":"ref40","first-page":"7537","article-title":"Fourier features let networks learn high frequency functions in low dimensional domains","volume":"33","author":"Tancik","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref41","article-title":"Hyperinr: A fast and predictive hypernetwork for implicit neural representations via knowledge distillation","author":"Wu","year":"2023","journal-title":"arXiv preprint"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.634"},{"key":"ref43","article-title":"Generative neural fields by mixtures of neural implicit functions","volume":"36","author":"You","year":"2024","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01863"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00612"},{"key":"ref46","article-title":"mixup: Beyond empirical risk minimization","volume-title":"International Conference on Learning Representations","author":"Zhang","year":"2018"},{"key":"ref47","article-title":"Vision mamba: Efficient visual representation learning with bidirectional state space model","volume-title":"Forty-first International Conference on Machine Learning","author":"Zhu","year":"2024"},{"key":"ref48","article-title":"Diffusion probabilistic fields","volume-title":"The Eleventh International Conference on Learning Representations","author":"Zhuang","year":"2023"},{"key":"ref49","first-page":"7693","article-title":"Fast context adaptation via meta-learning","volume-title":"International Conference on Machine Learning","author":"Zintgraf"}],"event":{"name":"2025 IEEE\/CVF International Conference on Computer Vision (ICCV)","location":"Honolulu, HI, USA","start":{"date-parts":[[2025,10,19]]},"end":{"date-parts":[[2025,10,25]]}},"container-title":["2025 IEEE\/CVF International Conference on Computer Vision (ICCV)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11443115\/11443287\/11444733.pdf?arnumber=11444733","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T05:07:16Z","timestamp":1777612036000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11444733\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,19]]},"references-count":49,"URL":"https:\/\/doi.org\/10.1109\/iccv51701.2025.00459","relation":{},"subject":[],"published":{"date-parts":[[2025,10,19]]}}}