{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,25]],"date-time":"2025-04-25T19:10:07Z","timestamp":1745608207251,"version":"3.40.4"},"publisher-location":"Singapore","reference-count":36,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819658084","type":"print"},{"value":"9789819658091","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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\/978-981-96-5809-1_11","type":"book-chapter","created":{"date-parts":[[2025,4,25]],"date-time":"2025-04-25T18:34:11Z","timestamp":1745606051000},"page":"192-211","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["LightStar-Net: A Pseudo-Raw Space Enhancement for\u00a0Efficient Low-Light Object Detection"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1105-3901","authenticated-orcid":false,"given":"Xin","family":"Feng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-2615-6051","authenticated-orcid":false,"given":"Jie","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siping","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiehui","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,4,26]]},"reference":[{"key":"11_CR1","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: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 12504\u201312513 (2023)","DOI":"10.1109\/ICCV51070.2023.01149"},{"key":"11_CR2","doi-asserted-by":"crossref","unstructured":"Chen, C., Chen, Q., Xu, J., Koltun, V.: Learning to see in the dark. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3291\u20133300 (2018)","DOI":"10.1109\/CVPR.2018.00347"},{"key":"11_CR3","unstructured":"Cui, Z., et al.: You only need 90k parameters to adapt light: a light weight transformer for image enhancement and exposure correction. arXiv preprint arXiv:2205.14871 (2022)"},{"key":"11_CR4","doi-asserted-by":"crossref","unstructured":"Cui, Z., Qi, G.J., Gu, L., You, S., Zhang, Z., Harada, T.: Multitask AET with orthogonal tangent regularity for dark object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 2553\u20132562 (2021)","DOI":"10.1109\/ICCV48922.2021.00255"},{"key":"11_CR5","unstructured":"Dai, J., Li, Y., He, K., Sun, J.: R-FCN: object detection via region-based fully convolutional networks. In: Advances in Neural Information Processing Systems, vol. 29 (2016)"},{"key":"11_CR6","doi-asserted-by":"crossref","unstructured":"Du, Z., Shi, M., Deng, J.: Boosting object detection with zero-shot day-night domain adaptation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12666\u201312676 (2024)","DOI":"10.1109\/CVPR52733.2024.01204"},{"key":"11_CR7","doi-asserted-by":"crossref","unstructured":"Fu, Z., Yang, Y., Tu, X., Huang, Y., Ding, X., Ma, K.K.: Learning a simple low-light image enhancer from paired low-light instances. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 22252\u201322261 (2023)","DOI":"10.1109\/CVPR52729.2023.02131"},{"key":"11_CR8","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 580\u2013587 (2014)","DOI":"10.1109\/CVPR.2014.81"},{"key":"11_CR9","doi-asserted-by":"crossref","unstructured":"Guo, C., et al.: Zero-reference deep curve estimation for low-light image enhancement. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1780\u20131789 (2020)","DOI":"10.1109\/CVPR42600.2020.00185"},{"key":"11_CR10","doi-asserted-by":"crossref","unstructured":"Hashmi, K.A., Kallempudi, G., Stricker, D., Afzal, M.Z.: Featenhancer: enhancing hierarchical features for object detection and beyond under low-light vision. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 6725\u20136735 (2023)","DOI":"10.1109\/ICCV51070.2023.00619"},{"issue":"7","key":"11_CR11","doi-asserted-by":"publisher","first-page":"1956","DOI":"10.1007\/s11263-020-01316-z","volume":"128","author":"A Kuznetsova","year":"2020","unstructured":"Kuznetsova, A., et al.: The open images dataset v4: unified image classification, object detection, and visual relationship detection at scale. Int. J. Comput. Vision 128(7), 1956\u20131981 (2020)","journal-title":"Int. J. Comput. Vision"},{"key":"11_CR12","doi-asserted-by":"crossref","unstructured":"Li, Z., Yi, S., Ma, Z.: Rendering nighttime image via cascaded color and brightness compensation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 897\u2013905 (2022)","DOI":"10.1109\/CVPRW56347.2022.00104"},{"key":"11_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1007\/978-3-319-10602-1_48","volume-title":"Computer Vision \u2013 ECCV 2014","author":"T-Y Lin","year":"2014","unstructured":"Lin, T.-Y., et al.: Microsoft COCO: common objects in context. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8693, pp. 740\u2013755. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10602-1_48"},{"key":"11_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/978-3-319-46448-0_2","volume-title":"Computer Vision \u2013 ECCV 2016","author":"W Liu","year":"2016","unstructured":"Liu, W., et al.: SSD: single shot multibox detector. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 21\u201337. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46448-0_2"},{"key":"11_CR15","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1016\/j.cviu.2018.10.010","volume":"178","author":"YP Loh","year":"2019","unstructured":"Loh, Y.P., Chan, C.S.: Getting to know low-light images with the exclusively dark dataset. Comput. Vis. Image Underst. 178, 30\u201342 (2019)","journal-title":"Comput. Vis. Image Underst."},{"key":"11_CR16","doi-asserted-by":"publisher","first-page":"650","DOI":"10.1016\/j.patcog.2016.06.008","volume":"61","author":"KG Lore","year":"2017","unstructured":"Lore, K.G., Akintayo, A., Sarkar, S.: LlNet: a deep autoencoder approach to natural low-light image enhancement. Pattern Recogn. 61, 650\u2013662 (2017)","journal-title":"Pattern Recogn."},{"key":"11_CR17","unstructured":"Lv, F., Lu, F., Wu, J., Lim, C.: MBLLEN: low-light image\/video enhancement using CNNs. In: BMVC, vol.\u00a0220, p.\u00a04. Northumbria University (2018)"},{"key":"11_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: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5637\u20135646 (2022)","DOI":"10.1109\/CVPR52688.2022.00555"},{"key":"11_CR19","doi-asserted-by":"crossref","unstructured":"Ouyang, D., et al.: Efficient multi-scale attention module with cross-spatial learning. In: ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.\u00a01\u20135. IEEE (2023)","DOI":"10.1109\/ICASSP49357.2023.10096516"},{"key":"11_CR20","doi-asserted-by":"crossref","unstructured":"Qin, Q., Chang, K., Huang, M., Li, G.: DeNet: detection-driven enhancement network for object detection under adverse weather conditions. In: Proceedings of the Asian Conference on Computer Vision, pp. 2813\u20132829 (2022)","DOI":"10.1007\/978-3-031-26313-2_30"},{"key":"11_CR21","unstructured":"Redmon, J., Farhadi, A.: Yolov3: an incremental improvement. arXiv preprint arXiv:1804.02767 (2018)"},{"key":"11_CR22","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. In: Advances in Neural Information Processing Systems, vol. 28 (2015)"},{"key":"11_CR23","first-page":"4461","volume":"35","author":"S Sun","year":"2022","unstructured":"Sun, S., Ren, W., Wang, T., Cao, X.: Rethinking image restoration for object detection. Adv. Neural. Inf. Process. Syst. 35, 4461\u20134474 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"11_CR24","doi-asserted-by":"crossref","unstructured":"Tian, Z., Shen, C., Chen, H., He, T.: FCOS: fully convolutional one-stage object detection. arxiv 2019. arXiv preprint arXiv:1904.01355 (1904)","DOI":"10.1109\/ICCV.2019.00972"},{"key":"11_CR25","doi-asserted-by":"crossref","unstructured":"Tung, F., Mori, G.: Similarity-preserving knowledge distillation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1365\u20131374 (2019)","DOI":"10.1109\/ICCV.2019.00145"},{"key":"11_CR26","doi-asserted-by":"crossref","unstructured":"Wang, C., Wu, H., Jin, Z.: FourLLIE: boosting low-light image enhancement by Fourier frequency information. In: Proceedings of the 31st ACM International Conference on Multimedia, pp. 7459\u20137469 (2023)","DOI":"10.1145\/3581783.3611909"},{"key":"11_CR27","doi-asserted-by":"crossref","unstructured":"Wang, Q., Wu, B., Zhu, P., Li, P., Zuo, W., Hu, Q.: ECA-net: efficient channel attention for deep convolutional neural networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11534\u201311542 (2020)","DOI":"10.1109\/CVPR42600.2020.01155"},{"key":"11_CR28","unstructured":"Wei, C., Wang, W., Yang, W., Liu, J.: Deep Retinex decomposition for low-light enhancement. arXiv preprint arXiv:1808.04560 (2018)"},{"key":"11_CR29","doi-asserted-by":"crossref","unstructured":"Wu, Y., et al.: Learning semantic-aware knowledge guidance for low-light image enhancement. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1662\u20131671 (2023)","DOI":"10.1109\/CVPR52729.2023.00166"},{"key":"11_CR30","doi-asserted-by":"crossref","unstructured":"Xing, Y., Qian, Z., Chen, Q.: Invertible image signal processing. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6287\u20136296 (2021)","DOI":"10.1109\/CVPR46437.2021.00622"},{"key":"11_CR31","doi-asserted-by":"publisher","first-page":"5737","DOI":"10.1109\/TIP.2020.2981922","volume":"29","author":"W Yang","year":"2020","unstructured":"Yang, W., et al.: Advancing image understanding in poor visibility environments: a collective benchmark study. IEEE Trans. Image Process. 29, 5737\u20135752 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"11_CR32","doi-asserted-by":"crossref","unstructured":"Yi, X., Xu, H., Zhang, H., Tang, L., Ma, J.: Diff-Retinex: rethinking low-light image enhancement with a generative diffusion model. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 12302\u201312311 (2023)","DOI":"10.1109\/ICCV51070.2023.01130"},{"key":"11_CR33","doi-asserted-by":"crossref","unstructured":"Yin, X., Yu, Z., Fei, Z., Lv, W., Gao, X.: PE-YOLO: pyramid enhancement network for dark object detection. In: International Conference on Artificial Neural Networks, pp. 163\u2013174. Springer (2023)","DOI":"10.1007\/978-3-031-44195-0_14"},{"key":"11_CR34","doi-asserted-by":"crossref","unstructured":"Zamir, S.W., et al.: CycleISP: real image restoration via improved data synthesis. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2696\u20132705 (2020)","DOI":"10.1109\/CVPR42600.2020.00277"},{"key":"11_CR35","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Zhang, J., Guo, X.: Kindling the darkness: a practical low-light image enhancer. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 1632\u20131640 (2019)","DOI":"10.1145\/3343031.3350926"},{"key":"11_CR36","doi-asserted-by":"crossref","unstructured":"Zhou, D., Yang, Z., Yang, Y.: Pyramid diffusion models for low-light image enhancement. arXiv preprint arXiv:2305.10028 (2023)","DOI":"10.24963\/ijcai.2023\/199"}],"container-title":["Lecture Notes in Computer Science","Computational Visual Media"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-5809-1_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,25]],"date-time":"2025-04-25T18:34:34Z","timestamp":1745606074000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-5809-1_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819658084","9789819658091"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-5809-1_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"26 April 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CVM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Visual Media","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hong Kong SAR","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 April 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 April 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cvm2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/iccvm.org\/2025\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}