{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T16:28:19Z","timestamp":1771950499324,"version":"3.50.1"},"reference-count":102,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["DP240101848"],"award-info":[{"award-number":["DP240101848"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["FT230100549"],"award-info":[{"award-number":["FT230100549"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1109\/tpami.2024.3406907","type":"journal-article","created":{"date-parts":[[2024,5,29]],"date-time":"2024-05-29T17:28:02Z","timestamp":1717003682000},"page":"8502-8516","source":"Crossref","is-referenced-by-count":4,"title":["Weak Augmentation Guided Relational Self-Supervised Learning"],"prefix":"10.1109","volume":"46","author":[{"given":"Mingkai","family":"Zheng","sequence":"first","affiliation":[{"name":"School of Computer Science, Faculty of Engineering, The University of Sydney, Camperdown, NSW, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1964-0430","authenticated-orcid":false,"given":"Shan","family":"You","sequence":"additional","affiliation":[{"name":"SenseTime Research, Shanghai, China"}]},{"given":"Fei","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, Anhui, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8761-5563","authenticated-orcid":false,"given":"Chen","family":"Qian","sequence":"additional","affiliation":[{"name":"SenseTime Research, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8088-367X","authenticated-orcid":false,"given":"Changshui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Automation, Institute for Artificial Intelligence, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8402-7504","authenticated-orcid":false,"given":"Xiaogang","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4756-0609","authenticated-orcid":false,"given":"Chang","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Computer Science, Faculty of Engineering, The University of Sydney, Camperdown, NSW, Australia"}]}],"member":"263","reference":[{"key":"ref1","first-page":"12980","article-title":"Compress: Self-supervised learning by compressing representations","volume":"33","author":"Koohpayegani","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref2","article-title":"A theoretical analysis of contrastive unsupervised representation learning","author":"Arora","year":"2019"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19836-6_20"},{"key":"ref4","first-page":"37","article-title":"Autoencoders, unsupervised learning and deep architectures","volume-title":"Proc. Int. Conf. Unsupervised Transfer Learn. Workshop","author":"Baldi"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10599-4_29"},{"key":"ref6","article-title":"Large scale GAN training for high fidelity natural image synthesis","author":"Brock","year":"2019"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01264-9_9"},{"key":"ref8","first-page":"9912","article-title":"Unsupervised learning of visual features by contrasting cluster assignments","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Caron"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00951"},{"key":"ref10","article-title":"A simple framework for contrastive learning of visual representations","author":"Chen","year":"2020"},{"key":"ref11","article-title":"Big self-supervised models are strong semi-supervised learners","author":"Chen","year":"2020"},{"key":"ref12","article-title":"Improved baselines with momentum contrastive learning","author":"Chen","year":"2020"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01549"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/iccv48922.2021.00950"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11783"},{"key":"ref16","first-page":"24645","article-title":"Unsupervised representation transfer for small networks: I believe i can distill on-the-fly","volume":"34","author":"Choi","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref17","first-page":"8765","article-title":"Debiased contrastive learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Chuang"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.461"},{"key":"ref19","first-page":"215","article-title":"An analysis of single-layer networks in unsupervised feature learning","volume-title":"Proc. Conf. Mach. Learn. Res.","author":"Coates"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2019.00020"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00359"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00482"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.167"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.167"},{"key":"ref26","first-page":"10542","article-title":"Large scale adversarial representation learning","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Donahue"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2010.11929"},{"key":"ref28","first-page":"12345","article-title":"Agree to disagree: Adaptive ensemble knowledge distillation in gradient space","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Du"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00945"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-019-10163-0"},{"key":"ref31","first-page":"3015","article-title":"Whitening for self-supervised representation learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Ermolov"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref33","first-page":"1","article-title":"{SEED}: Self-supervised distillation for visual representation","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Fang"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2004.383"},{"key":"ref35","article-title":"Disco: Remedy self-supervised learning on lightweight models with distilled contrastive learning","author":"Gao","year":"2021"},{"key":"ref36","article-title":"Unsupervised representation learning by predicting image rotations","author":"Gidaris","year":"2018"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.5555\/2969033.2969125"},{"key":"ref38","article-title":"Bootstrap your own latent: A new approach to self-supervised learning","author":"Grill","year":"2020"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"ref40","article-title":"Momentum contrast for unsupervised visual representation learning","author":"He","year":"2019"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref42","article-title":"Deep residual learning for image recognition","author":"He","year":"2015"},{"key":"ref43","article-title":"Distilling the knowledge in a neural network","author":"Hinton","year":"2015"},{"key":"ref44","article-title":"Learning deep representations by mutual information estimation and maximization","author":"Hjelm","year":"2018"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00140"},{"key":"ref46","article-title":"AdCo: Adversarial contrast for efficient learning of unsupervised representations from self-trained negative adversaries","author":"Hu","year":"2020"},{"key":"ref47","article-title":"Self-adaptive training: Bridging the supervised and self-supervised learning","author":"Huang","year":"2021"},{"key":"ref48","article-title":"Boosting contrastive self-supervised learning with false negative cancellation","author":"Huynh","year":"2020"},{"key":"ref49","first-page":"21798","article-title":"Hard negative mixing for contrastive learning","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Kalantidis"},{"key":"ref50","article-title":"Supervised contrastive learning","author":"Khosla","year":"2020"},{"key":"ref51","first-page":"1","article-title":"Auto-encoding variational bayes","volume-title":"Proc. 2nd Int. Conf. Learn. Representations","author":"Kingma"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2013.77"},{"key":"ref53","article-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"key":"ref54","article-title":"Contrastive predictive coding based feature for automatic speaker verification","author":"Lai","year":"2019"},{"issue":"7","key":"ref55","article-title":"Tiny ImageNet visual recognition challenge","volume":"7","author":"Le","year":"2015","journal-title":"CS 231N"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.19"},{"key":"ref57","first-page":"5714","article-title":"Self-supervised label augmentation via input transformations","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Lee"},{"key":"ref58","first-page":"1","article-title":"Prototypical contrastive learning of unsupervised representations","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Li"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1007\/BF01589116"},{"key":"ref61","article-title":"Self-supervised learning: Generative or contrastive","author":"Liu","year":"2020"},{"key":"ref62","article-title":"SGDR: Stochastic gradient descent with warm restarts","author":"Loshchilov","year":"2016"},{"key":"ref63","article-title":"Fine-grained visual classification of aircraft","author":"Maji","year":"2013"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00943"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00674"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/ICVGIP.2008.47"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46466-4_5"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00409"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6248092"},{"key":"ref70","article-title":"FixMatch: Simplifying semi-supervised learning with consistency and confidence","author":"Sohn","year":"2020"},{"key":"ref71","first-page":"6105","article-title":"EfficientNet: Rethinking model scaling for convolutional neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Tan"},{"key":"ref72","article-title":"Exploring the equivalence of Siamese self-supervised learning via a unified gradient framework","author":"Tao","year":"2021"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00947"},{"key":"ref74","article-title":"Contrastive multiview coding","author":"Tian","year":"2019"},{"key":"ref75","article-title":"What makes for good views for contrastive learning?","author":"Tian","year":"2020"},{"key":"ref76","first-page":"10347","article-title":"Training data-efficient image transformers distillation through attention","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Touvron"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00145"},{"issue":"11","key":"ref78","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123359"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00937"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00552"},{"key":"ref82","article-title":"Understanding contrastive representation learning through alignment and uniformity on the hypersphere","author":"Wang","year":"2020"},{"key":"ref83","article-title":"Contrastive learning with stronger augmentations","author":"Wang","year":"2021"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01240"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01647"},{"key":"ref86","first-page":"3502","article-title":"CroCo: Self-supervised pre-training for 3D vision tasks by cross-view completion","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Weinzaepfel"},{"key":"ref87","article-title":"Detectron2","author":"Wu","year":"2019"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00393"},{"key":"ref89","first-page":"6256","article-title":"Unsupervised data augmentation for consistency training","volume":"33","author":"Xie","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref90","first-page":"1","article-title":"Bag of instances aggregation boosts self-supervised distillation","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Xu"},{"key":"ref91","first-page":"1","article-title":"Self-labelling via simultaneous clustering and representation learning","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Asano"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098135"},{"key":"ref93","article-title":"Large batch training of convolutional networks","author":"You","year":"2017"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00302"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00391"},{"key":"ref96","first-page":"12310","article-title":"Barlow twins: Self-supervised learning via redundancy reduction","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Zbontar"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00156"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46487-9_40"},{"key":"ref99","article-title":"Self-supervised representation learning via adaptive hard-positive mining","author":"Zhang","year":"2021"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00989"},{"key":"ref101","article-title":"Relational self-supervised learning with weak augmentation","author":"Zheng","year":"2021"},{"key":"ref102","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00610"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/10746266\/10540667.pdf?arnumber=10540667","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:23:06Z","timestamp":1732666986000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10540667\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12]]},"references-count":102,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2024.3406907","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"value":"0162-8828","type":"print"},{"value":"2160-9292","type":"electronic"},{"value":"1939-3539","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12]]}}}