{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T10:02:57Z","timestamp":1766138577532,"version":"3.37.3"},"reference-count":70,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2024,2,7]],"date-time":"2024-02-07T00:00:00Z","timestamp":1707264000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,2,7]],"date-time":"2024-02-07T00:00:00Z","timestamp":1707264000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1007\/s00371-023-03255-5","type":"journal-article","created":{"date-parts":[[2024,2,7]],"date-time":"2024-02-07T13:02:47Z","timestamp":1707310967000},"page":"8573-8589","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Image inpainting based on fusion structure information and pixelwise attention"],"prefix":"10.1007","volume":"40","author":[{"given":"Dan","family":"Wu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1859-9096","authenticated-orcid":false,"given":"Jixiang","family":"Cheng","sequence":"additional","affiliation":[]},{"given":"Zhidan","family":"Li","sequence":"additional","affiliation":[]},{"given":"Zhou","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,2,7]]},"reference":[{"key":"3255_CR1","doi-asserted-by":"crossref","unstructured":"Zhang, H., Mai, L., Xu, N., Wang, Z., Collomosse, J., Jin, H.: An internal learning approach to video inpainting. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 2720\u20132729 (2019)","DOI":"10.1109\/ICCV.2019.00281"},{"issue":"11","key":"3255_CR2","doi-asserted-by":"publisher","first-page":"2646","DOI":"10.1007\/s11263-022-01665-x","volume":"130","author":"T Yu","year":"2022","unstructured":"Yu, T., Lin, C., Zhang, S., Wang, C., Ding, X., An, H., Liu, X., Ting, Q., Wan, L., You, S., et al.: Artificial intelligence for Dunhuang cultural heritage protection: the project and the dataset. Int. J. Comput. Vis. 130(11), 2646\u20132673 (2022)","journal-title":"Int. J. Comput. Vis."},{"key":"3255_CR3","doi-asserted-by":"publisher","first-page":"4369","DOI":"10.1109\/JSTARS.2020.3012443","volume":"13","author":"R Wong","year":"2020","unstructured":"Wong, R., Zhang, Z., Wang, Y., Chen, F., Zeng, D.: HSI-IPNet: hyperspectral imagery inpainting by deep learning with adaptive spectral extraction. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 13, 4369\u20134380 (2020)","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"3255_CR4","doi-asserted-by":"crossref","unstructured":"K\u0131nl\u0131, F., \u00d6zcan, B., K\u0131ra\u00e7, F.: A benchmark for inpainting of clothing images with irregular holes. In: Proceedings of the European Conference on Computer Vision, pp. 182\u2013199 (2020)","DOI":"10.1007\/978-3-030-66823-5_11"},{"issue":"3","key":"3255_CR5","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1109\/TIFS.2017.2763119","volume":"13","author":"S Zhang","year":"2017","unstructured":"Zhang, S., He, R., Sun, Z., Tan, T.: Demeshnet: blind face inpainting for deep meshface verification. IEEE Trans. Inf. Forensics Secur. 13(3), 637\u2013647 (2017)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"issue":"1","key":"3255_CR6","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1109\/MSP.2013.2273004","volume":"31","author":"C Guillemot","year":"2013","unstructured":"Guillemot, C., Le Meur, O.: Image inpainting: overview and recent advances. IEEE Signal Process. Mag. 31(1), 127\u2013144 (2013)","journal-title":"IEEE Signal Process. Mag."},{"issue":"2","key":"3255_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.displa.2021.102028","volume":"69","author":"Z Qin","year":"2021","unstructured":"Qin, Z., Zeng, Q., Zong, Y., Fan, X.: Image inpainting based on deep learning: a review. Displays 69(2), 102028 (2021)","journal-title":"Displays"},{"key":"3255_CR8","doi-asserted-by":"crossref","unstructured":"Bertalmio, M., Bertozzi, A.L., Sapiro, G.: Navier\u2013stokes, fluid dynamics, and image and video inpainting. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 355\u2013362 (2001)","DOI":"10.1109\/CVPR.2001.990497"},{"issue":"1","key":"3255_CR9","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1109\/TGRS.2012.2237521","volume":"52","author":"Q Cheng","year":"2013","unstructured":"Cheng, Q., Shen, H., Zhang, L., Li, P.: Inpainting for remotely sensed images with a multichannel nonlocal total variation model. IEEE Trans. Geosci. Remote Sens. 52(1), 175\u2013187 (2013)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"3255_CR10","doi-asserted-by":"crossref","unstructured":"Arya, A.S., Saha, A., Mukhopadhyay, S.: ADMM optimizer for integrating wavelet-patch and group-based sparse representation for image inpainting. Vis. Comput. (2023)","DOI":"10.1007\/s00371-023-02786-1"},{"key":"3255_CR11","doi-asserted-by":"crossref","unstructured":"Criminisi, A., Perez, P., Toyama, K.: Object removal by exemplar-based inpainting. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 721\u2013728 (2003)","DOI":"10.1109\/CVPR.2003.1211538"},{"issue":"11","key":"3255_CR12","doi-asserted-by":"publisher","first-page":"2649","DOI":"10.1109\/TIP.2007.906269","volume":"16","author":"N Komodakis","year":"2007","unstructured":"Komodakis, N., Tziritas, G.: Image completion using efficient belief propagation via priority scheduling and dynamic pruning. IEEE Trans. Image Process. 16(11), 2649\u20132661 (2007)","journal-title":"IEEE Trans. Image Process."},{"key":"3255_CR13","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1016\/j.inffus.2022.08.033","volume":"90","author":"X Zhang","year":"2022","unstructured":"Zhang, X., Zhai, D., Li, T., Zhou, Y., Lin, Y.: Image inpainting based on deep learning: a review. Inf. Fusion 90, 74\u201394 (2022)","journal-title":"Inf. Fusion"},{"key":"3255_CR14","doi-asserted-by":"crossref","unstructured":"Pathak, D., Krahenbuhl, P., Donahue, J., Darrell, T., Efros, A.A.: Context encoders: feature learning by inpainting. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2536\u20132544 (2016)","DOI":"10.1109\/CVPR.2016.278"},{"issue":"4","key":"3255_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3072959.3073659","volume":"36","author":"S Iizuka","year":"2017","unstructured":"Iizuka, S., Simo-Serra, E., Ishikawa, H.: Globally and locally consistent image completion. ACM Trans. Graph. 36(4), 1\u201314 (2017)","journal-title":"ACM Trans. Graph."},{"issue":"8","key":"3255_CR16","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.patrec.2020.12.008","volume":"143","author":"W Liu","year":"2021","unstructured":"Liu, W., Cao, C., Liu, J., Ren, C., Wei, Y., Guo, H.: Fine-grained image inpainting with scale-enhanced generative adversarial network. Pattern Recogn. Lett. 143(8), 81\u201387 (2021)","journal-title":"Pattern Recogn. Lett."},{"key":"3255_CR17","doi-asserted-by":"crossref","unstructured":"Liu, G., Reda, F.A., Shih, K.J., Wang, T.-C., Andrew, T., Bryan, C.: Image inpainting for irregular holes using partial convolutions. In: Proceedings of the European Conference on Computer Vision, pp. 85\u2013100 (2018)","DOI":"10.1007\/978-3-030-01252-6_6"},{"issue":"12","key":"3255_CR18","doi-asserted-by":"publisher","first-page":"4398","DOI":"10.1109\/TCYB.2018.2865036","volume":"49","author":"H Li","year":"2018","unstructured":"Li, H., Li, G., Lin, L., Hongchuan, Y., Yizhou, Y.: Context-aware semantic inpainting. IEEE Trans. Cybern. 49(12), 4398\u20134411 (2018)","journal-title":"IEEE Trans. Cybern."},{"issue":"6","key":"3255_CR19","doi-asserted-by":"publisher","first-page":"3460","DOI":"10.1007\/s10489-020-01971-2","volume":"51","author":"Y Chen","year":"2021","unstructured":"Chen, Y., Zhang, H., Liu, L., Chen, X., Zhang, Q., Yang, K., Xia, R., Xie, J.: Research on image inpainting algorithm of improved GAN based on two-discriminations networks. Appl. Intell. 51(6), 3460\u20133474 (2021)","journal-title":"Appl. Intell."},{"issue":"8","key":"3255_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2020.103155","volume":"204","author":"J Qin","year":"2021","unstructured":"Qin, J., Bai, H., Zhao, Y.: Multi-scale attention network for image inpainting. Comput. Vis. Image Underst. 204(8), 103155 (2021)","journal-title":"Comput. Vis. Image Underst."},{"key":"3255_CR21","doi-asserted-by":"crossref","unstructured":"Cao, C., Dong, Q., Fu, Y.: Learning prior feature and attention enhanced image inpainting. In: Proceedings of the European Conference on Computer Vision, pp. 306\u2013322 (2022)","DOI":"10.1007\/978-3-031-19784-0_18"},{"key":"3255_CR22","doi-asserted-by":"crossref","unstructured":"Yu, J., Lin, Z., Yang, J., Shen, X., Lu, X., Huang, T.S.: Generative image inpainting with contextual attention. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5505\u20135514 (2018)","DOI":"10.1109\/CVPR.2018.00577"},{"key":"3255_CR23","doi-asserted-by":"crossref","unstructured":"Liu, H., Jiang, B., Xiao, Y., Yang, C.: Coherent semantic attention for image inpainting. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4170\u20134179 (2019)","DOI":"10.1109\/ICCV.2019.00427"},{"issue":"4","key":"3255_CR24","first-page":"220","volume":"402","author":"X Liming","year":"2020","unstructured":"Liming, X., Zeng, X., Li, W., Huang, Z.: Multi-granularity generative adversarial nets with reconstructive sampling for image inpainting. Neurocomputing 402(4), 220\u2013234 (2020)","journal-title":"Neurocomputing"},{"key":"3255_CR25","unstructured":"Nazeri, K., Ng, E., Joseph, T., Qureshi, F.Z., Ebrahimi, M.: EdgeConnect: generative image inpainting with adversarial edge learning. arXiv:1901.00212 (2019)"},{"issue":"4","key":"3255_CR26","first-page":"1308","volume":"31","author":"X Shunxin","year":"2020","unstructured":"Shunxin, X., Liu, D., Xiong, Z.: E2I: generative inpainting from edge to image. IEEE Trans. Circuits Syst. Video Technol. 31(4), 1308\u20131322 (2020)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"3255_CR27","doi-asserted-by":"crossref","unstructured":"Xiong, W., Yu, J., Lin, Z., Yang, J., Lu, X., Barnes, C., Luo, J.: Foreground-aware image inpainting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5840\u20135848 (2019)","DOI":"10.1109\/CVPR.2019.00599"},{"key":"3255_CR28","unstructured":"Song, Y., Yang, C., Shen, Y., Wang, P., Huang, Q., Kuo, C.-C.J.: SPG-Net: segmentation prediction and guidance network for image inpainting. arXiv:1805.03356 (2018)"},{"issue":"3","key":"3255_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.image.2020.115929","volume":"87","author":"H Shao","year":"2020","unstructured":"Shao, H., Wang, Y., Yinghua, F., Yin, Z.: Generative image inpainting via edge structure and color aware fusion. Signal Process. Image Commun. 87(3), 115929 (2020)","journal-title":"Signal Process. Image Commun."},{"issue":"4","key":"3255_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.image.2021.116148","volume":"93","author":"MA Hedjazi","year":"2021","unstructured":"Hedjazi, M.A., Genc, Y.: Image inpainting using scene constraints. Signal Process. Image Commun. 93(4), 116148 (2021)","journal-title":"Signal Process. Image Commun."},{"key":"3255_CR31","doi-asserted-by":"crossref","unstructured":"Dong, Q., Cao, C., Fu, Y.: Incremental transformer structure enhanced image inpainting with masking positional encoding. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11358\u201311368 (2022)","DOI":"10.1109\/CVPR52688.2022.01107"},{"key":"3255_CR32","first-page":"329","volume":"31","author":"Y Wang","year":"2018","unstructured":"Wang, Y., Tao, X., Qi, X., Shen, X., Jia, J.: Image inpainting via generative multi-column convolutional neural networks. Adv. Neural. Inf. Process. Syst. 31, 329\u2013338 (2018)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"3255_CR33","doi-asserted-by":"crossref","unstructured":"Ni, M., Li, X., Zuo, W.: NUWA-LIP: language-guided image inpainting with defect-free VQGAN. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 14183\u201314192 (2023)","DOI":"10.1109\/CVPR52729.2023.01363"},{"key":"3255_CR34","doi-asserted-by":"publisher","first-page":"1784","DOI":"10.1109\/TIP.2020.3048629","volume":"30","author":"N Wang","year":"2021","unstructured":"Wang, N., Zhang, Y., Zhang, L.: Dynamic selection network for image inpainting. IEEE Trans. Image Process. 30, 1784\u20131798 (2021)","journal-title":"IEEE Trans. Image Process."},{"issue":"99","key":"3255_CR35","doi-asserted-by":"publisher","first-page":"842","DOI":"10.1109\/LSP.2021.3070738","volume":"28","author":"M Chen","year":"2021","unstructured":"Chen, M., Liu, Z.: EDBGAN: image inpainting via an edge-aware dual branch generative adversarial network. IEEE Signal Process. Lett. 28(99), 842\u2013846 (2021)","journal-title":"IEEE Signal Process. Lett."},{"key":"3255_CR36","doi-asserted-by":"crossref","unstructured":"Wang, Z., Li, K., Peng, J.: Dynamic context-driven progressive image inpainting with auxiliary generative units. Vis. Comput. (2023)","DOI":"10.1007\/s00371-023-03045-z"},{"key":"3255_CR37","doi-asserted-by":"crossref","unstructured":"Zeng, Y., Lin, Z., Yang, J., Zhang, J., Shechtman, E., Lu, H.: High-resolution image inpainting with iterative confidence feedback and guided upsampling. In: Proceedings of the European Conference on Computer Vision, pp. 1\u201317 (2020)","DOI":"10.1007\/978-3-030-58529-7_1"},{"key":"3255_CR38","doi-asserted-by":"crossref","unstructured":"Li, J., Wang, N., Zhang, L., Du, B., Tao, D.: Recurrent feature reasoning for image inpainting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7760\u20137768 (2020)","DOI":"10.1109\/CVPR42600.2020.00778"},{"key":"3255_CR39","doi-asserted-by":"crossref","unstructured":"Zeng, Y., Fu, J., Chao, H., Guo, B.: Learning pyramid-context encoder network for high-quality image inpainting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1486\u20131494 (2019)","DOI":"10.1109\/CVPR.2019.00158"},{"key":"3255_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106789","volume":"217","author":"MA Hedjazi","year":"2021","unstructured":"Hedjazi, M.A., Genc, Y.: Efficient texture-aware multi-GAN for image inpainting. Knowl.-Based Syst. 217, 106789 (2021)","journal-title":"Knowl.-Based Syst."},{"issue":"1","key":"3255_CR41","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1109\/TNNLS.2020.2978501","volume":"32","author":"Y-G Shin","year":"2020","unstructured":"Shin, Y.-G., Sagong, M.-C., Yeo, Y.-J., Kim, S.-W., Ko, S.-J.: PEPSI++: fast and lightweight network for image inpainting. IEEE Trans. Neural Netw. Learn. Syst. 32(1), 252\u2013265 (2020)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"3255_CR42","doi-asserted-by":"crossref","unstructured":"Xie, C., Liu, S., Li, C., Cheng, M.-M., Zuo, W., Liu, X., Wen, S., Ding, E.: Image inpainting with learnable bidirectional attention maps. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 8858\u20138867 (2019)","DOI":"10.1109\/ICCV.2019.00895"},{"key":"3255_CR43","doi-asserted-by":"publisher","first-page":"3816","DOI":"10.1109\/ACCESS.2020.3047740","volume":"9","author":"L Sun","year":"2020","unstructured":"Sun, L., Zhang, Q., Wang, W., Zhang, M.: Image inpainting with learnable edge-attention maps. IEEE Access 9, 3816\u20133827 (2020)","journal-title":"IEEE Access"},{"key":"3255_CR44","doi-asserted-by":"crossref","unstructured":"Yang, J., Qi, Z., Shi, Y.: Learning to incorporate structure knowledge for image inpainting. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 12605\u201312612 (2020)","DOI":"10.1609\/aaai.v34i07.6951"},{"key":"3255_CR45","doi-asserted-by":"crossref","unstructured":"Yu, Y., Du, D., Zhang, L., Luo, T.: Unbiased multi-modality guidance for image inpainting. In: Proceedings of the European Conference on Computer Vision, pp. 668\u2013684. Springer (2022)","DOI":"10.1007\/978-3-031-19787-1_38"},{"issue":"11","key":"3255_CR46","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1145\/3422622","volume":"63","author":"I Goodfellow","year":"2020","unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., Bing, X., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial networks. Commun. ACM 63(11), 139\u2013144 (2020)","journal-title":"Commun. ACM"},{"key":"3255_CR47","unstructured":"Hui, Z., Li, J., Wang, X., Gao, X.: Image fine-grained inpainting. arXiv preprint arXiv:2002.02609 (2020)"},{"key":"3255_CR48","unstructured":"Demir, U., Unal, G.: Patch-based image inpainting with generative adversarial networks. arXiv preprint arXiv:1803.07422 (2018)"},{"key":"3255_CR49","doi-asserted-by":"publisher","first-page":"2647","DOI":"10.1007\/s00371-021-02143-0","volume":"38","author":"Y Yang","year":"2022","unstructured":"Yang, Y., Cheng, Z., Haotian, Y., Zhang, Y., Cheng, X., Zhang, Z., Xie, G.: MSE-Net: generative image inpainting with multi-scale encoder. Vis. Comput. 38, 2647\u20132659 (2022)","journal-title":"Vis. Comput."},{"key":"3255_CR50","doi-asserted-by":"crossref","unstructured":"Liao, L., Xiao, J., Wang, Z., Lin, C.-W., Satoh, S.: Image inpainting guided by coherence priors of semantics and textures. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6539\u20136548 (2021)","DOI":"10.1109\/CVPR46437.2021.00647"},{"key":"3255_CR51","doi-asserted-by":"publisher","first-page":"3149","DOI":"10.1007\/s00371-022-02523-0","volume":"38","author":"Y Xie","year":"2022","unstructured":"Xie, Y., Lin, Z., Yang, Z., Deng, H., Xingcai, W., Mao, X., Li, Q., Liu, W.: Learning semantic alignment from image for text-guided image inpainting. Vis. Comput. 38, 3149\u20133161 (2022)","journal-title":"Vis. Comput."},{"key":"3255_CR52","doi-asserted-by":"crossref","unstructured":"Li, W., Lin, Z., Zhou, K., Qi, L., Wang, Y., Jia, J.: MAT: mask-aware transformer for large hole image inpainting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10758\u201310768 (2022)","DOI":"10.1109\/CVPR52688.2022.01049"},{"key":"3255_CR53","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1016\/j.neucom.2020.03.090","volume":"405","author":"M Chen","year":"2020","unstructured":"Chen, M., Liu, Z., Ye, L., Wang, Y.: Attentional coarse-and-fine generative adversarial networks for image inpainting. Neurocomputing 405, 259\u2013269 (2020)","journal-title":"Neurocomputing"},{"key":"3255_CR54","doi-asserted-by":"crossref","unstructured":"Li, J., He, F., Zhang, L., Du, B., Tao, D.: Progressive reconstruction of visual structure for image inpainting. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 5962\u20135971 (2019)","DOI":"10.1109\/ICCV.2019.00606"},{"issue":"6","key":"3255_CR55","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2366145.2366213","volume":"31","author":"X Li","year":"2012","unstructured":"Li, X., Yan, Q., Xia, Y., Jia, J.: Structure extraction from texture via relative total variation. ACM Trans. Graph. 31(6), 1\u201310 (2012)","journal-title":"ACM Trans. Graph."},{"issue":"6","key":"3255_CR56","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","volume":"8","author":"J Canny","year":"1986","unstructured":"Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8(6), 679\u2013698 (1986)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3255_CR57","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7132\u20137141 (2018)","DOI":"10.1109\/CVPR.2018.00745"},{"key":"3255_CR58","unstructured":"Miyato, T., Kataoka, T., Koyama, M., Yoshida, Y.: Spectral normalization for generative adversarial networks. arXiv:1802.05957 (2018)"},{"key":"3255_CR59","unstructured":"Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., Courville, A.C.: Improved training of wasserstein gans. Adv. Neural Inf. Process. Syst. 30 (2017)"},{"issue":"6","key":"3255_CR60","doi-asserted-by":"publisher","first-page":"1452","DOI":"10.1109\/TPAMI.2017.2723009","volume":"40","author":"B Zhou","year":"2017","unstructured":"Zhou, B., Lapedriza, A., Khosla, A., Oliva, A., Torralba, A.: Places: a 10 million image database for scene recognition. IEEE Trans. Pattern Anal. Mach. Intell. 40(6), 1452\u20131464 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3255_CR61","doi-asserted-by":"crossref","unstructured":"Liu, Z., Luo, P., Wang, X., Tang, X.: Deep learning face attributes in the wild. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3730\u20133738 (2015)","DOI":"10.1109\/ICCV.2015.425"},{"issue":"4","key":"3255_CR62","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2185520.2185597","volume":"31","author":"C Doersch","year":"2012","unstructured":"Doersch, C., Singh, S., Gupta, A., Sivic, J., Efros, A.: What makes Paris look like Paris? ACM Trans. Graph. 31(4), 1\u20139 (2012)","journal-title":"ACM Trans. Graph."},{"key":"3255_CR63","doi-asserted-by":"crossref","unstructured":"Liu, H., Jiang, B., Song, Y., Huang, W., Yang, C.: Rethinking image inpainting via a mutual encoder-decoder with feature equalizations. In: Proceedings of the European Conference on Computer Vision, pp. 725\u2013741 (2020)","DOI":"10.1007\/978-3-030-58536-5_43"},{"key":"3255_CR64","doi-asserted-by":"crossref","unstructured":"Guo, X., Yang, H., Huang, D.: Image inpainting via conditional texture and structure dual generation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 14134\u201314143 (2021)","DOI":"10.1109\/ICCV48922.2021.01387"},{"key":"3255_CR65","doi-asserted-by":"crossref","unstructured":"Li, X., Guo, Q., Lin, D., Li, P., Feng, W., Wang, S.: MISF: multi-level interactive Siamese filtering for high-fidelity image inpainting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1869\u20131878 (2022)","DOI":"10.1109\/CVPR52688.2022.00191"},{"key":"3255_CR66","doi-asserted-by":"crossref","unstructured":"Jain, J., Zhou, Y., Yu, N., Shi, H.: Keys to better image inpainting: structure and texture go hand in hand. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 208\u2013217 (2023)","DOI":"10.1109\/WACV56688.2023.00029"},{"key":"3255_CR67","doi-asserted-by":"crossref","unstructured":"Yu, Y., Zhan, F., Wu, R., Pan, J., Cui, K., Lu, S., Ma, F., Xie, X., Miao, C.: Diverse image inpainting with bidirectional and autoregressive transformers. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 69\u201378 (2021)","DOI":"10.1145\/3474085.3475436"},{"key":"3255_CR68","first-page":"25","volume":"8","author":"M Heusel","year":"2017","unstructured":"Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., Hochreiter, S.: Gans trained by a two time-scale update rule converge to a local nash equilibrium. Asian J. Appl. Sci. Eng. 8, 25\u201334 (2017)","journal-title":"Asian J. Appl. Sci. Eng."},{"key":"3255_CR69","doi-asserted-by":"crossref","unstructured":"Zhang, R., Isola, P., Efros, A.A., Shechtman, E., Wang, O.: The unreasonable effectiveness of deep features as a perceptual metric. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 586\u2013595 (2018)","DOI":"10.1109\/CVPR.2018.00068"},{"key":"3255_CR70","doi-asserted-by":"crossref","unstructured":"Yu, J., Lin, Z., Yang, J., Shen, X., Lu, X., Huang, T.S.: Free-form image inpainting with gated convolution. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp. 4471\u20134480 (2019)","DOI":"10.1109\/ICCV.2019.00457"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-023-03255-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-023-03255-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-023-03255-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T09:07:33Z","timestamp":1731402453000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-023-03255-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,7]]},"references-count":70,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2024,12]]}},"alternative-id":["3255"],"URL":"https:\/\/doi.org\/10.1007\/s00371-023-03255-5","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"type":"print","value":"0178-2789"},{"type":"electronic","value":"1432-2315"}],"subject":[],"published":{"date-parts":[[2024,2,7]]},"assertion":[{"value":"25 December 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 February 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no relevant financial or nonfinancial interests to disclose.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent:"}}]}}