{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T04:00:11Z","timestamp":1781841611877,"version":"3.54.5"},"reference-count":91,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"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","award":["62076067"],"award-info":[{"award-number":["62076067"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62176061"],"award-info":[{"award-number":["62176061"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003399","name":"Science and Technology Commission of Shanghai Municipality","doi-asserted-by":"publisher","award":["22511105000"],"award-info":[{"award-number":["22511105000"]}],"id":[{"id":"10.13039\/501100003399","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":[[2023,10]]},"DOI":"10.1109\/tpami.2023.3280222","type":"journal-article","created":{"date-parts":[[2023,5,26]],"date-time":"2023-05-26T17:42:52Z","timestamp":1685122972000},"page":"12667-12684","source":"Crossref","is-referenced-by-count":62,"title":["ZITS++: Image Inpainting by Improving the Incremental Transformer on Structural Priors"],"prefix":"10.1109","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3916-2843","authenticated-orcid":false,"given":"Chenjie","family":"Cao","sequence":"first","affiliation":[{"name":"School of Data Science, MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3083-5143","authenticated-orcid":false,"given":"Qiaole","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Data Science, MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6595-6893","authenticated-orcid":false,"given":"Yanwei","family":"Fu","sequence":"additional","affiliation":[{"name":"School of Data Science, MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01107"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/wacv51458.2022.00323"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1986.4767851"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3084197"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00408"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01424"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01387"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-019-10163-0"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00183"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/344779.344972"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2003.1238360"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.160"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/1276377.1276382"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2003.1211538"},{"key":"ref15","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Krizhevsky"},{"key":"ref16","article-title":"Generative adversarial nets","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"27","author":"Goodfellow"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00465"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00753"},{"key":"ref19","article-title":"Large scale image completion via co-modulated generative adversarial networks","author":"Zhao","year":"2021"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01049"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00577"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58529-7_1"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475436"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58583-9_41"},{"key":"ref25","article-title":"SPG-NET: Segmentation prediction and guidance network for image inpainting","author":"Song","year":"2018"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00027"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58536-5_43"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2020.3001267"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6951"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/183"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00072"},{"key":"ref32","article-title":"How much position information do convolutional neural networks encode?","author":"Islam","year":"2020"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01336"},{"key":"ref34","article-title":"InfinityGAN: Towards infinite-pixel image synthesis","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Lin","year":"2022"},{"key":"ref35","first-page":"1352","article-title":"ReZero is all you need: Fast convergence at large depth","volume-title":"Proc. Uncertainty Artif. Intell.","author":"Bachlechner"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/s41095-023-0364-2"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.164"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/2366145.2366158"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.177"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2723009"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33715-4_54"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2017.00081"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00453"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2017.2730822"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2014.2372479"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.278"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01252-6_6"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00457"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/tvcg.2022.3156949"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00813"},{"key":"ref51","first-page":"8780","article-title":"Diffusion models beat GANs on image synthesis","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Dhariwal"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1145\/3528233.3530757"},{"key":"ref54","article-title":"Glide: Towards photorealistic image generation and editing with text-guided diffusion models","author":"Nichol","year":"2021"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01117"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01209"},{"key":"ref57","article-title":"Improving diffusion models for inverse problems using manifold constraints","author":"Chung","year":"2022"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58610-2_42"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01704"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19797-0_5"},{"key":"ref61","first-page":"1691","article-title":"Generative pretraining from pixels","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Chen"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref63","article-title":"An image is worth 16x16 words: Transformers for image recognition at scale","author":"Dosovitskiy","year":"2020"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01268"},{"key":"ref65","first-page":"8821","article-title":"Zero-shot text-to-image generation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Ramesh","year":"2021"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"ref67","first-page":"4479","article-title":"Fast Fourier convolution","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Chi"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52688.2022.01166"},{"key":"ref69","article-title":"More convnets in the 2020s: Scaling up kernels beyond 51x51 using sparsity","author":"Liu","year":"2022"},{"key":"ref70","first-page":"30392","article-title":"Early convolutions help transformers see better","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Xiao"},{"key":"ref71","article-title":"Axial attention in multidimensional transformers","author":"Ho","year":"2019"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00069"},{"key":"ref73","article-title":"Exploring the limits of transfer learning with a unified text-to-text transformer","author":"Raffel","year":"2019"},{"key":"ref74","first-page":"10 524","article-title":"On layer normalization in the transformer architecture","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Xiong"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00286"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_26"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref78","article-title":"Searching for activation functions","author":"Ramachandran","year":"2017"},{"key":"ref79","article-title":"Multi-scale context aggregation by dilated convolutions","author":"Yu","year":"2015"},{"key":"ref80","article-title":"Improved training of Wasserstein GANs","author":"Gulrajani","year":"2017"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00917"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1633"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00105"},{"key":"ref84","article-title":"Dense extreme inception network for edge detection","author":"Poma","year":"2021"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-018-1140-0"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00681"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.151"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"ref89","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":"Adv. Neural Inf. Process. Syst."},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00068"},{"key":"ref91","article-title":"Feature refinement to improve high resolution image inpainting","author":"Kulshreshtha","year":"2022"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/10241246\/10136788.pdf?arnumber=10136788","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,7]],"date-time":"2024-06-07T17:29:57Z","timestamp":1717781397000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10136788\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10]]},"references-count":91,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2023.3280222","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":[[2023,10]]}}}