{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T13:03:05Z","timestamp":1742994185733,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":36,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819601219"},{"type":"electronic","value":"9789819601226"}],"license":[{"start":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T00:00:00Z","timestamp":1731369600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T00:00:00Z","timestamp":1731369600000},"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":[[2025]]},"DOI":"10.1007\/978-981-96-0122-6_19","type":"book-chapter","created":{"date-parts":[[2024,11,16]],"date-time":"2024-11-16T18:24:29Z","timestamp":1731781469000},"page":"208-219","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["HQPAFT: Enhancing Low-Light Images with\u00a0High-Quality Priors and\u00a0Advanced Feature Transformations Using Only Normal Light Images"],"prefix":"10.1007","author":[{"given":"Zeyu","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hanxiang","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sheng","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiongxin","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fanjiang","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiao","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,11,12]]},"reference":[{"key":"19_CR1","unstructured":"Aghajanzadeh, S., Forsyth, D.: Long scale error control in low light image and video enhancement using equivariance (2022)"},{"key":"19_CR2","doi-asserted-by":"crossref","unstructured":"Bychkovsky, V., Paris, S., Chan, E., Durand, F.: Learning photographic global tonal adjustment with a database of input\/output image pairs. In: CVPR (2011)","DOI":"10.1109\/CVPR.2011.5995332"},{"key":"19_CR3","doi-asserted-by":"crossref","unstructured":"Cai, Y., Bian, H., Lin, J., Wang, H., Timofte, R., Zhang, Y.: Retinexformer: one-stage retinex-based transformer for low-light image enhancement. In: ICCV (2023)","DOI":"10.1109\/ICCV51070.2023.01149"},{"key":"19_CR4","doi-asserted-by":"crossref","unstructured":"Chen, C., Chen, Q., Xu, J., Koltun, V.: Learning to see in the dark. IEEE Conf. Comput. Vis. Pattern Recog. 3291\u20133300 (2018)","DOI":"10.1109\/CVPR.2018.00347"},{"key":"19_CR5","doi-asserted-by":"crossref","unstructured":"Du, Z., Shi, M., Deng, J.: Boosting object detection with zero-shot day-night domain adaptation. arXiv preprint arXiv:2312.01220 (2023)","DOI":"10.1109\/CVPR52733.2024.01204"},{"key":"19_CR6","doi-asserted-by":"crossref","unstructured":"Esser, P., Rombach, R., Ommer, B.: Taming transformers for high-resolution image synthesis. arXiv preprint arXiv:2012.09841 (2020)","DOI":"10.1109\/CVPR46437.2021.01268"},{"key":"19_CR7","doi-asserted-by":"crossref","unstructured":"Fu, Z., Yang, Y., Tu, X., Huang, Y., Ding, X., Ma, K.: Learning a simple low-light image enhancer from paired low-light instances. In: CVPR (2023)","DOI":"10.1109\/CVPR52729.2023.02131"},{"key":"19_CR8","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. In: Advances in Neural Information Processing Systems, pp. 2672\u20132680 (2014)"},{"key":"19_CR9","doi-asserted-by":"crossref","unstructured":"Guo, C.G., et al.: Zero-reference deep curve estimation for low-light image enhancement. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1780\u20131789 (2020)","DOI":"10.1109\/CVPR42600.2020.00185"},{"key":"19_CR10","doi-asserted-by":"crossref","unstructured":"Guo, X., Li, Y., Ling, H.: Lime: low-light image enhancement via illumination map estimation. IEEE Trans. Image Process. 26(2), 982\u2013993 (2016)","DOI":"10.1109\/TIP.2016.2639450"},{"key":"19_CR11","doi-asserted-by":"crossref","unstructured":"Jiang, Y., et al.: EnlightenGAN: deep light enhancement without paired supervision. IEEE TIP 30, 2340\u20132349 (2021)","DOI":"10.1109\/TIP.2021.3051462"},{"key":"19_CR12","doi-asserted-by":"publisher","unstructured":"Jin, Y., Yang, W., Tan, R.T.: Unsupervised night image enhancement: when layer decomposition meets light-effects suppression. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022, Part XXXVII, pp. 404\u2013421. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19836-6_23","DOI":"10.1007\/978-3-031-19836-6_23"},{"issue":"6","key":"19_CR13","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1038\/scientificamerican1277-108","volume":"237","author":"EH Land","year":"1977","unstructured":"Land, E.H.: The retinex theory of color vision. Sci. Am. 237(6), 108\u2013129 (1977)","journal-title":"Sci. Am."},{"issue":"1","key":"19_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1364\/JOSA.61.000001","volume":"61","author":"EH Land","year":"1971","unstructured":"Land, E.H., McCann, J.J.: Lightness and retinex theory. JOSA 61(1), 1\u201311 (1971)","journal-title":"JOSA"},{"issue":"8","key":"19_CR15","first-page":"4225","volume":"44","author":"C Li","year":"2021","unstructured":"Li, C., Guo, C., Loy, C.C.: Learning to enhance low-light image via zero-reference deep curve estimation. IEEE TPAMI 44(8), 4225\u20134238 (2021)","journal-title":"IEEE TPAMI"},{"key":"19_CR16","doi-asserted-by":"crossref","unstructured":"Liang, Z., Li, C., Zhou, S., Feng, R., Loy, C.C.: Iterative prompt learning for unsupervised backlit image enhancement. In: ICCV (2023)","DOI":"10.1109\/ICCV51070.2023.00743"},{"key":"19_CR17","doi-asserted-by":"crossref","unstructured":"Liu, R., Ma, L., Zhang, J., Fan, X., Luo, Z.: Retinex-inspired unrolling with cooperative prior architecture search for low-light image enhancement. In: CVPR (2021)","DOI":"10.1109\/CVPR46437.2021.01042"},{"key":"19_CR18","doi-asserted-by":"crossref","unstructured":"Ma, L., Ma, T., Liu, R., Fan, X., Luo, Z.: Toward fast, flexible, and robust low-light image enhancement. In: CVPR (2022)","DOI":"10.1109\/CVPR52688.2022.00555"},{"key":"19_CR19","unstructured":"van\u00a0den Oord, A., Vinyals, O., Kavukcuoglu, K.: Neural discrete representation learning (2018)"},{"issue":"1","key":"19_CR20","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1117\/1.1636183","volume":"13","author":"DJ Jobson","year":"2004","unstructured":"Jobson, D.J.: Retinex processing for automatic image enhancement. J. Electron. Imaging 13(1), 100 (2004). https:\/\/doi.org\/10.1117\/1.1636183","journal-title":"J. Electron. Imaging"},{"key":"19_CR21","unstructured":"Sun, S., Ren, W., Peng, J., Song, F., Cao, X.: Di-retinex: digital-imaging retinex theory for low-light image enhancement (2024)"},{"key":"19_CR22","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, pp. 5998\u20136008 (2017)"},{"key":"19_CR23","doi-asserted-by":"crossref","unstructured":"Wang, C., Wu, H., Jin, Z.: Fourllie: boosting low-light image enhancement by Fourier frequency information. arXiv preprint arXiv:2308.03033 (2023)","DOI":"10.1145\/3581783.3611909"},{"key":"19_CR24","doi-asserted-by":"crossref","unstructured":"Wang, W., Yang, H., Fu, J., Liu, J.: Zero-reference low-light enhancement via physical quadruple priors (2024)","DOI":"10.1109\/CVPR52733.2024.02462"},{"key":"19_CR25","unstructured":"Wei, C., Wang, W., Yang, W., Liu, J.: Deep retinex decomposition for low-light enhancement. In: BMVC (2018)"},{"key":"19_CR26","doi-asserted-by":"crossref","unstructured":"Wu, R., Duan, Z., Guo, C., Chai, Z., Li, C.: Ridcp: revitalizing real image dehazing via high-quality codebook priors. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2023)","DOI":"10.1109\/CVPR52729.2023.02134"},{"key":"19_CR27","doi-asserted-by":"crossref","unstructured":"Wu, W., Weng, J., Zhang, P., Wang, X., Yang, W., Jiang, J.: Uretinex-net: retinex-based deep unfolding network for low-light image enhancement. In: CVPR (2022)","DOI":"10.1109\/CVPR52688.2022.00581"},{"key":"19_CR28","doi-asserted-by":"crossref","unstructured":"Yang, S., Ding, M., Wu, Y., Li, Z., Zhang, J.: Implicit neural representation for cooperative low-light image enhancement. In: ICCV (2023)","DOI":"10.1109\/ICCV51070.2023.01187"},{"key":"19_CR29","doi-asserted-by":"crossref","unstructured":"Yang, W., Wang, S., Fang, Y., Wang, Y., Liu, J.: From fidelity to perceptual quality: a semi-supervised approach for low-light image enhancement. In: CVPR (2020)","DOI":"10.1109\/CVPR42600.2020.00313"},{"key":"19_CR30","doi-asserted-by":"crossref","unstructured":"Zhang, L., Zhang, L., Liu, X., Shen, Y., Zhang, S., Zhao, S.: Zero-shot restoration of back-lit images using deep internal learning. In: ACM MM (2019)","DOI":"10.1145\/3343031.3351069"},{"key":"19_CR31","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 Conference on Computer Vision and Pattern Recognition, pp. 586\u2013595 (2018)","DOI":"10.1109\/CVPR.2018.00068"},{"issue":"4","key":"19_CR32","first-page":"1013","volume":"129","author":"Y Zhang","year":"2021","unstructured":"Zhang, Y., Guo, X., Ma, J., Liu, W., Zhang, J.: Beyond brightening low-light images. IJCV 129(4), 1013\u20131037 (2021)","journal-title":"Beyond brightening low-light images. IJCV"},{"key":"19_CR33","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Zhang, J., Guo, X.: Kindling the darkness: a practical low-light image enhancer. In: ACM MM (2019)","DOI":"10.1145\/3343031.3350926"},{"issue":"3","key":"19_CR34","doi-asserted-by":"publisher","first-page":"1076","DOI":"10.1109\/TCSVT.2021.3073371","volume":"32","author":"Z Zhao","year":"2022","unstructured":"Zhao, Z., Xiong, B., Wang, L., Ou, Q., Yu, L., Kuang, F.: Retinexdip: a unified deep framework for low-light image enhancement. IEEE Trans. Circuits Syst. Video Technol. 32(3), 1076\u20131088 (2022). https:\/\/doi.org\/10.1109\/TCSVT.2021.3073371","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"19_CR35","doi-asserted-by":"publisher","unstructured":"Zhou, S., Li, C., Change Loy, C.: LEDNet: joint low-light enhancement and\u00a0deblurring in\u00a0the\u00a0dark. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022, Part VI, pp. 573\u2013589. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-20068-7_33","DOI":"10.1007\/978-3-031-20068-7_33"},{"key":"19_CR36","doi-asserted-by":"crossref","unstructured":"Zou, W., et al.: Vqcnir: clearer night image restoration with vector-quantized codebook. arXiv preprint arXiv:2312.08606 (2023)","DOI":"10.1609\/aaai.v38i7.28623"}],"container-title":["Lecture Notes in Computer Science","PRICAI 2024: Trends in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-0122-6_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,16]],"date-time":"2024-11-16T19:19:09Z","timestamp":1731784749000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-0122-6_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,12]]},"ISBN":["9789819601219","9789819601226"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-0122-6_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,11,12]]},"assertion":[{"value":"12 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRICAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific Rim International Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kyoto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 November 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 November 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pricai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.pricai.org\/2024\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}