{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T20:21:58Z","timestamp":1740169318417,"version":"3.37.3"},"reference-count":62,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001870","name":"Foundation for Polish Science","doi-asserted-by":"crossref","award":["POIR.04.04.00-00-14DE\/18-00"],"award-info":[{"award-number":["POIR.04.04.00-00-14DE\/18-00"]}],"id":[{"id":"10.13039\/501100001870","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100004281","name":"National Science Centre, Poland","doi-asserted-by":"publisher","award":["2020\/39\/B\/ST6\/01511"],"award-info":[{"award-number":["2020\/39\/B\/ST6\/01511"]}],"id":[{"id":"10.13039\/501100004281","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004281","name":"National Science Centre, Poland","doi-asserted-by":"publisher","award":["2018\/31\/N\/ST6\/02273"],"award-info":[{"award-number":["2018\/31\/N\/ST6\/02273"]}],"id":[{"id":"10.13039\/501100004281","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3242982","type":"journal-article","created":{"date-parts":[[2023,2,6]],"date-time":"2023-02-06T18:58:04Z","timestamp":1675709884000},"page":"13028-13043","source":"Crossref","is-referenced-by-count":0,"title":["Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7234-393X","authenticated-orcid":false,"given":"Witold","family":"Oleszkiewicz","sequence":"first","affiliation":[{"name":"Warsaw University of Technology, Warszawa, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dominika","family":"Basaj","sequence":"additional","affiliation":[{"name":"Warsaw University of Technology, Warszawa, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Igor","family":"Sieradzki","sequence":"additional","affiliation":[{"name":"Faculty of Mathematics and Computer Science, Jagiellonian University, Kraków, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Micha","family":"Gorszczak","sequence":"additional","affiliation":[{"name":"Faculty of Mathematics and Computer Science, Jagiellonian University, Kraków, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2336-5347","authenticated-orcid":false,"given":"Barbara","family":"Rychalska","sequence":"additional","affiliation":[{"name":"Warsaw University of Technology, Warszawa, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Koryna","family":"Lewandowska","sequence":"additional","affiliation":[{"name":"Cognitive Neuroscience and Neuroergonomics, Institute of Applied Psychology, Kraków, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1486-8906","authenticated-orcid":false,"given":"Tomasz","family":"Trzcinski","sequence":"additional","affiliation":[{"name":"Warsaw University of Technology, Warszawa, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3063-3621","authenticated-orcid":false,"given":"Bartosz","family":"Zielinski","sequence":"additional","affiliation":[{"name":"Faculty of Mathematics and Computer Science, Jagiellonian University, Kraków, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Big self-supervised models are strong semi-supervised learners","author":"Chen","year":"2020","journal-title":"arXiv:2006.10029"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1573"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N19-1419"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S19-1026"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1275"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.586"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/11957959_7"},{"key":"ref9","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"25","author":"Krizhevsky"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.279"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1631\/FITEE.1700808"},{"key":"ref12","article-title":"Understanding intermediate layers using linear classifier probes","author":"Alain","year":"2016","journal-title":"arXiv:1610.01644"},{"key":"ref13","article-title":"Sanity checks for saliency maps","author":"Adebayo","year":"2018","journal-title":"arXiv:1810.03292"},{"key":"ref14","article-title":"Deep inside convolutional networks: Visualising image classification models and saliency maps","author":"Simonyan","year":"2013","journal-title":"arXiv:1312.6034"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00869"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.771"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-3022"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1198"},{"key":"ref19","article-title":"Towards automatic concept-based explanations","author":"Ghorbani","year":"2019","journal-title":"arXiv:1902.03129"},{"key":"ref20","article-title":"Bootstrap your own latent: A new approach to self-supervised learning","author":"Grill","year":"2020","journal-title":"arXiv:2006.07733"},{"key":"ref21","article-title":"Unsupervised learning of visual features by contrasting cluster assignments","author":"Caron","year":"2020","journal-title":"arXiv:2006.09882"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1023\/A:1022459009182","article-title":"How picture books work: A semiotically framed theory of text-picture relationships","volume":"29","author":"Sipe","year":"1998","journal-title":"Children\u2019s Literature in Educ."},{"key":"ref23","article-title":"An image is worth 16 \u00d7 16 words: Transformers for image recognition at scale","author":"Dosovitskiy","year":"2020","journal-title":"arXiv:2010.11929"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1023\/A:1011126920638","article-title":"Representing and recognizing the visual appearance of materials using three-dimensional textons","volume":"43","author":"Leung","year":"2001","journal-title":"Int. J. Comput. Vis."},{"key":"ref26","first-page":"2668","article-title":"Interpretability beyond feature attribution: Quantitative testing with concept activation vectors (TCAV)","volume-title":"Proc. 35th Int. Conf. Mach. Learn.","author":"Kim"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.120"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.100"},{"key":"ref31","article-title":"On the surprising similarities between supervised and self-supervised models","author":"Geirhos","year":"2020","journal-title":"arXiv:2010.08377"},{"key":"ref32","article-title":"Using self-supervised learning can improve model robustness and uncertainty","author":"Hendrycks","year":"2019","journal-title":"arXiv:1906.12340"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.5555\/3524938.3525087"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2005.09.004"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1086\/289413"},{"volume-title":"Vision: A Computational Investigation into the Human Representation and Processing of Visual Information","year":"1982","author":"Marr","key":"ref36"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1037\/0003-066X.44.12.1469"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.visres.2010.08.002"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939778"},{"key":"ref40","article-title":"Understanding deep image representations by inverting them","author":"Mahendran","year":"2014","journal-title":"arXiv:1412.0035"},{"key":"ref41","article-title":"Grad-CAM++: Generalized gradient-based visual explanations for deep convolutional networks","author":"Chattopadhyay","year":"2017","journal-title":"arXiv:1710.11063"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.354"},{"key":"ref43","article-title":"Interpreting deep visual representations via network dissection","author":"Zhou","year":"2017","journal-title":"arXiv:1711.05611"},{"key":"ref44","article-title":"This looks like that: Deep learning for interpretable image recognition","author":"Chen","year":"2018","journal-title":"arXiv:1806.10574"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46487-9_40"},{"key":"ref46","article-title":"Unsupervised representation learning by predicting image rotations","author":"Gidaris","year":"2018","journal-title":"arXiv:1803.07728"},{"volume-title":"VISSL","year":"2021","author":"Goyal","key":"ref47"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00254"},{"key":"ref49","first-page":"930","article-title":"Measuring and evaluating the compactness of superpixels","volume-title":"Proc. 21st Int. Conf. Pattern Recognit. (ICPR)","author":"Schick"},{"key":"ref50","first-page":"1","article-title":"Fast superpixel segmentation using morphological processing","volume-title":"Proc. Int. Conf. Mach. Vis. Mach. Learn.","author":"Benesova"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/82"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1023\/b:visi.0000029664.99615.94"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2011.222"},{"key":"ref54","article-title":"When explanations lie: Why many modified BP attributions fail","author":"Sixt","year":"2019","journal-title":"arXiv:1912.09818"},{"article-title":"Visual analysis of degree-of-interest functions to support selection strategies for instance labeling","volume-title":"Proc. EuroVA, Int. Workshop Vis. Anal.","author":"Bernard","key":"ref55"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-3020"},{"key":"ref57","first-page":"1","article-title":"One-shot learning with a hierarchical nonparametric Bayesian model","volume-title":"Proc. ICML UTL Workshop","author":"Salakhutdinov"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467245"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300234"},{"key":"ref60","first-page":"1","article-title":"Explaining and harnessing adversarial examples","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Goodfellow"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1002\/nme.1620141104"},{"key":"ref62","article-title":"Hierarchical text-conditional image generation with CLIP latents","author":"Ramesh","year":"2022","journal-title":"arXiv:2204.06125"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10038644.pdf?arnumber=10038644","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,2]],"date-time":"2024-03-02T18:40:35Z","timestamp":1709404835000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10038644\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":62,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3242982","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2023]]}}}