{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T07:04:01Z","timestamp":1784358241457,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":20,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819235124","type":"print"},{"value":"9789819235131","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"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":[],"published-print":{"date-parts":[[2027]]},"DOI":"10.1007\/978-981-92-3513-1_10","type":"book-chapter","created":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T06:41:52Z","timestamp":1784356912000},"page":"115-126","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Spatially-Aware Guidance for High-Fidelity Text-Guided Image Inpainting with Diffusion Models"],"prefix":"10.1007","author":[{"given":"Zhu","family":"Liang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunmei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,19]]},"reference":[{"key":"10_CR1","unstructured":"Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. In: Advances in Neural Information Processing Systems, pp. 6840\u20136851 (2020)"},{"key":"10_CR2","doi-asserted-by":"crossref","unstructured":"Liu, H., Wan, Z., Huang, W., et al.: PD-GAN: probabilistic diverse GAN for image inpainting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9371\u20139381 (2021)","DOI":"10.1109\/CVPR46437.2021.00925"},{"key":"10_CR3","doi-asserted-by":"crossref","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., et al.: High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10684\u201310695 (2022)","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"10_CR4","doi-asserted-by":"crossref","unstructured":"Razzhigaev, A., Shakhmatov, A., Maltseva, A., et al.: Kandinsky: an improved text-to-image synthesis with image prior and latent diffusion. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 286\u2013295 (2023)","DOI":"10.18653\/v1\/2023.emnlp-demo.25"},{"key":"10_CR5","unstructured":"Yang, S., Zhang, L., Ma, L., et al.: MagicRemover: tuning-free text-guided image inpainting with diffusion models. arXiv preprint arXiv:2310.02848 (2023)"},{"key":"10_CR6","unstructured":"Dhariwal, P., Nichol, A.: Diffusion models beat GANs on image synthesis. In: Advances in Neural Information Processing Systems, pp. 8780\u20138794 (2021)"},{"key":"10_CR7","doi-asserted-by":"crossref","unstructured":"Epstein, D., Jabri, A., Poole, B., et al.: Diffusion self-guidance for controllable image generation. In: Advances in Neural Information Processing Systems, pp. 16222\u201316239 (2023)","DOI":"10.52202\/075280-0714"},{"key":"10_CR8","unstructured":"Ho, J., Salimans, T.: Classifier-free diffusion guidance. In: NeurIPS Workshop on Deep Generative Models and Downstream Applications (2021)"},{"key":"10_CR9","doi-asserted-by":"crossref","unstructured":"Xie, S., Zhang, Z., Lin, Z., et al.: SmartBrush: text- and shape-guided object inpainting with diffusion model. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 22428\u201322437 (2023)","DOI":"10.1109\/CVPR52729.2023.02148"},{"key":"10_CR10","doi-asserted-by":"crossref","unstructured":"Zhuang, J., Zeng, Y., Liu, W., et al.: A task is worth one word: learning with task prompts for high-quality versatile image inpainting. In: Proceedings of the European Conference on Computer Vision, pp. 195\u2013211 (2024)","DOI":"10.1007\/978-3-031-73636-0_12"},{"key":"10_CR11","doi-asserted-by":"crossref","unstructured":"Shen, D., Song, G., Xue, Z., et al.: Rethinking the spatial inconsistency in classifier-free diffusion guidance. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9370\u20139379 (2024)","DOI":"10.1109\/CVPR52733.2024.00895"},{"key":"10_CR12","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Maire, M., Belongie, S., et al.: Microsoft COCO: common objects in context. In: Proceedings of the European Conference on Computer Vision, pp. 740\u2013755 (2014)","DOI":"10.1007\/978-3-319-10602-1_48"},{"issue":"7","key":"10_CR13","doi-asserted-by":"publisher","first-page":"1956","DOI":"10.1007\/s11263-020-01316-z","volume":"128","author":"A Kuznetsova","year":"2020","unstructured":"Kuznetsova, A., Rom, H., Alldrin, N., et al.: The Open Images dataset V4: unified image classification, object detection, and visual relationship detection at scale. Int. J. Comput. Vis. 128(7), 1956\u20131981 (2020)","journal-title":"Int. J. Comput. Vis."},{"key":"10_CR14","doi-asserted-by":"crossref","unstructured":"Wang, S., Saharia, C., Montgomery, C., et al.: Imagen Editor and EditBench: advancing and evaluating text-guided image inpainting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 18359\u201318369 (2023)","DOI":"10.1109\/CVPR52729.2023.01761"},{"key":"10_CR15","doi-asserted-by":"crossref","unstructured":"Brooks, T., Holynski, A., Efros, A.A.: InstructPix2Pix: learning to follow image editing instructions. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 18392\u201318402 (2023)","DOI":"10.1109\/CVPR52729.2023.01764"},{"key":"10_CR16","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Medical Image Computing and Computer-Assisted Intervention, pp. 234\u2013241. Springer, Cham (2015)","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"10_CR17","unstructured":"Seitzer, M.: pytorch-fid: FID score for PyTorch. Version 0.3.0 (2020). https:\/\/github.com\/mseitzer\/pytorch-fid. Accessed 1 March 2026"},{"key":"10_CR18","unstructured":"Radford, A., Kim, J.W., Hallacy, C., et al.: Learning transferable visual models from natural language supervision. In: Proceedings of the International Conference on Machine Learning, pp. 8748\u20138763 (2021)"},{"key":"10_CR19","unstructured":"Patil, S., Cuenca, P., Lambert, N., et al.: Stable Diffusion with Diffusers. Hugging Face Blog (2022), https:\/\/huggingface.co\/blog\/stable_diffusion. Accessed 1 March 2026"},{"key":"10_CR20","unstructured":"Lykon: DreamShaper 8 Inpainting. Hugging Face (2023). https:\/\/huggingface.co\/Lykon\/dreamshaper-8-inpainting. Accessed 1 March 2026"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-3513-1_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T06:41:55Z","timestamp":1784356915000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-3513-1_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,19]]},"ISBN":["9789819235124","9789819235131"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-3513-1_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,19]]},"assertion":[{"value":"19 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toronto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2026a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2026\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}