{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T16:07:47Z","timestamp":1784218067693,"version":"3.55.0"},"reference-count":100,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100018623","name":"Quanzhou City Science and Technology Program","doi-asserted-by":"publisher","award":["2024QZC001R"],"award-info":[{"award-number":["2024QZC001R"]}],"id":[{"id":"10.13039\/501100018623","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100017357","name":"Science and Technology Projects of Fujian Province","doi-asserted-by":"publisher","award":["2024T3055"],"award-info":[{"award-number":["2024T3055"]}],"id":[{"id":"10.13039\/100017357","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100017357","name":"Science and Technology Projects of Fujian Province","doi-asserted-by":"publisher","award":["2025T3023"],"award-info":[{"award-number":["2025T3023"]}],"id":[{"id":"10.13039\/100017357","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003392","name":"Fujian Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["2025J01248"],"award-info":[{"award-number":["2025J01248"]}],"id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Applied Soft Computing"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.asoc.2026.115635","type":"journal-article","created":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T15:53:24Z","timestamp":1780415604000},"page":"115635","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PB","title":["RIFL-Net: A Retinex-guided illumination-invariant feature learning network for nighttime pedestrian detection"],"prefix":"10.1016","volume":"201","author":[{"given":"Jun","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huajian","family":"Cai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiming","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.asoc.2026.115635_bib0005","doi-asserted-by":"crossref","first-page":"1126","DOI":"10.1109\/TITS.2022.3155488","article-title":"Multifeature fusion-based object detection for intelligent transportation systems","volume":"24","author":"Yang","year":"2023","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.asoc.2026.115635_bib0010","doi-asserted-by":"crossref","first-page":"2260","DOI":"10.1109\/TCSVT.2016.2581660","article-title":"A low-complexity pedestrian detection framework for smart video surveillance systems","volume":"27","author":"Bilal","year":"2017","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.asoc.2026.115635_bib0015","doi-asserted-by":"crossref","first-page":"1595","DOI":"10.1109\/TCSVT.2017.2672686","article-title":"Variant SemiBoost for improving human detection in application scenes","volume":"28","author":"Wu","year":"2018","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.asoc.2026.115635_bib0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2021.108038","article-title":"Unsupervised domain-adaptive scene-specific pedestrian detection for static video surveillance","volume":"118","author":"Mou","year":"2021","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.asoc.2026.115635_bib0025","series-title":"2024 IEEE International Conference on Robotics and Automation (ICRA)","first-page":"4428","article-title":"A safety-adapted loss for pedestrian detection in autonomous driving","author":"Lyssenko","year":"2024"},{"key":"10.1016\/j.asoc.2026.115635_bib0030","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1109\/TCSVT.2021.3060162","article-title":"Deep cross-modal representation learning and distillation for illumination-invariant pedestrian detection","volume":"32","author":"Liu","year":"2022","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.asoc.2026.115635_bib0035","series-title":"2019 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"9556","article-title":"Discriminative feature transformation for occluded pedestrian detection","author":"Zhou","year":"2019"},{"key":"10.1016\/j.asoc.2026.115635_bib0040","series-title":"Advances in Neural Information Processing Systems, 33","first-page":"19953","article-title":"Beta R-CNN: looking into pedestrian detection from another perspective","author":"Xu","year":"2020"},{"key":"10.1016\/j.asoc.2026.115635_bib0045","series-title":"2022 26th International Conference on Pattern Recognition (ICPR)","first-page":"4658","article-title":"F2DNet: fast focal detection network for pedestrian detection","author":"Khan","year":"2022"},{"key":"10.1016\/j.asoc.2026.115635_bib0050","series-title":"2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"6662","article-title":"VLPD: context-aware pedestrian detection via vision-language semantic self-supervision","author":"Liu","year":"2023"},{"key":"10.1016\/j.asoc.2026.115635_bib0055","series-title":"2023 International Joint Conference on Neural Networks (IJCNN)","first-page":"1","article-title":"Camera coach: activity recognition and assessment using thermal and RGB videos","author":"Sharshar","year":"2023"},{"key":"10.1016\/j.asoc.2026.115635_bib0060","doi-asserted-by":"crossref","DOI":"10.1016\/j.jvcir.2019.102649","article-title":"Analyzing multiple types of behaviors from traffic videos via nonparametric topic model","volume":"64","author":"Zhou","year":"2019","journal-title":"J. Vis. Commun. Image Represent."},{"key":"10.1016\/j.asoc.2026.115635_bib0065","series-title":"Advances in Neural Information Processing Systems, 37","first-page":"87136","article-title":"You only look around: learning illumination-invariant feature for low-light object detection","author":"Hong","year":"2024"},{"key":"10.1016\/j.asoc.2026.115635_bib0070","doi-asserted-by":"crossref","unstructured":"Q. Qin, K. Chang, M. Huang, G. Li, DENet: detection-driven enhancement network for object detection under adverse weather conditions, 2022, pp. 491\u2013507, 10.1007\/978-3-031-26313-2_30","DOI":"10.1007\/978-3-031-26313-2_30"},{"key":"10.1016\/j.asoc.2026.115635_bib0075","author":"Yin"},{"key":"10.1016\/j.asoc.2026.115635_bib0080","author":"Cui"},{"key":"10.1016\/j.asoc.2026.115635_bib0085","series-title":"2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"1777","article-title":"Zero-reference deep curve estimation for low-light image enhancement","author":"Guo","year":"2020"},{"key":"10.1016\/j.asoc.2026.115635_bib0090","series-title":"2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"936","article-title":"Feature pyramid networks for object detection","author":"Lin","year":"2017"},{"key":"10.1016\/j.asoc.2026.115635_bib0095","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2023.110719","article-title":"Nighttime pedestrian detection based on fore-background contrast learning","volume":"275","author":"Yao","year":"2023","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.asoc.2026.115635_bib0100","doi-asserted-by":"crossref","first-page":"2003","DOI":"10.1109\/TIP.2022.3189803","article-title":"Pedestrian detection by exemplar-guided contrastive learning","volume":"32","author":"Lin","year":"2023","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.asoc.2026.115635_bib0105","series-title":"2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"5476","article-title":"Localized semantic feature mixers for efficient pedestrian detection in autonomous driving","author":"Khan","year":"2023"},{"key":"10.1016\/j.asoc.2026.115635_bib0110","doi-asserted-by":"crossref","first-page":"5372","DOI":"10.1109\/TIP.2013.2284059","article-title":"Contrast enhancement based on layered difference representation of 2D histograms","volume":"22","author":"Lee","year":"2013","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.asoc.2026.115635_bib0115","doi-asserted-by":"crossref","first-page":"2340","DOI":"10.1109\/TIP.2021.3051462","article-title":"EnlightenGAN: deep light enhancement without paired supervision","volume":"30","author":"Jiang","year":"2021","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.asoc.2026.115635_bib0120","doi-asserted-by":"crossref","first-page":"3078","DOI":"10.1073\/pnas.83.10.3078","article-title":"An alternative technique for the computation of the designator in the retinex theory of color vision","volume":"83","author":"Land","year":"1986","journal-title":"Proc. Natl. Acad. Sci."},{"key":"10.1016\/j.asoc.2026.115635_bib0125","author":"Wei"},{"key":"10.1016\/j.asoc.2026.115635_bib0130","series-title":"2021 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"2533","article-title":"Multitask AET with orthogonal tangent regularity for dark object detection","author":"Cui","year":"2021"},{"key":"10.1016\/j.asoc.2026.115635_bib0135","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1007\/s00530-025-01994-0","article-title":"Ihenet: an illumination invariant hierarchical feature enhancement network for low-light object detection","volume":"31","author":"Li","year":"2025","journal-title":"Multimed. Syst."},{"key":"10.1016\/j.asoc.2026.115635_bib0140","doi-asserted-by":"crossref","first-page":"6989","DOI":"10.1109\/TITS.2023.3264573","article-title":"A cross-scale and illumination invariance-based model for robust object detection in traffic surveillance scenarios","volume":"24","author":"Lu","year":"2023","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.asoc.2026.115635_bib0145","doi-asserted-by":"crossref","first-page":"3726","DOI":"10.3390\/s25123726","article-title":"HGCS-det: a deep learning-based solution for localizing and recognizing household garbage in complex scenarios","volume":"25","author":"Zhou","year":"2025","journal-title":"Sensors"},{"key":"10.1016\/j.asoc.2026.115635_bib0150","doi-asserted-by":"crossref","first-page":"5121","DOI":"10.1007\/s11760-024-03220-2","article-title":"YOLO-MTG: a lightweight YOLO model for multi-target garbage detection","volume":"18","author":"Xia","year":"2024","journal-title":"Signal Image Video Process."},{"key":"10.1016\/j.asoc.2026.115635_bib0155","doi-asserted-by":"crossref","first-page":"8739","DOI":"10.1007\/s11760-024-03511-8","article-title":"RCSFN: a remote sensing image scene classification and recognition network based on rectangle convolutional self attention fusion","volume":"18","author":"Hou","year":"2024","journal-title":"Signal Image Video Process."},{"key":"10.1016\/j.asoc.2026.115635_bib0160","doi-asserted-by":"crossref","first-page":"5960","DOI":"10.1080\/01431161.2023.2257861","article-title":"HPAC: a forest tree species recognition network based on multi-scale spatial enhancement in remote sensing images","volume":"44","author":"Hou","year":"2023","journal-title":"Int. J. Remote Sens."},{"key":"10.1016\/j.asoc.2026.115635_bib0165","doi-asserted-by":"crossref","unstructured":"L. Neumann, M. Karg, S. Zhang, C. Scharfenberger, E. Piegert, S. Mistr, O. Prokofyeva, R. Thiel, A. Vedaldi, A. Zisserman, B. Schiele, NightOwls: a pedestrians at night dataset, 2018, pp. 691\u2013705, 10.1007\/978-3-030-20887-5_43","DOI":"10.1007\/978-3-030-20887-5_43"},{"key":"10.1016\/j.asoc.2026.115635_bib0170","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1109\/TIP.2020.3034487","article-title":"TJU-DHD: a diverse high-resolution dataset for object detection","volume":"30","author":"Pang","year":"2021","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.asoc.2026.115635_bib0175","series-title":"2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"4457","article-title":"CityPersons: a diverse dataset for pedestrian detection","author":"Zhang","year":"2017"},{"key":"10.1016\/j.asoc.2026.115635_bib0180","doi-asserted-by":"crossref","first-page":"9398","DOI":"10.1109\/TMM.2024.3401549","article-title":"Consistent GT-proposal assignment for challenging pedestrian detection","volume":"26","author":"Luo","year":"2024","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.asoc.2026.115635_bib0185","doi-asserted-by":"crossref","first-page":"6061","DOI":"10.1109\/JSEN.2023.3242082","article-title":"Correlation-and-correction fusion attention network for occluded pedestrian detection","volume":"23","author":"Zou","year":"2023","journal-title":"IEEE Sens. J."},{"key":"10.1016\/j.asoc.2026.115635_bib0190","series-title":"2024 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"423","article-title":"PairDETR: joint detection and association of human bodies and faces","author":"Ali","year":"2024"},{"key":"10.1016\/j.asoc.2026.115635_bib0195","series-title":"2023 IEEE International Conference on Multimedia and Expo (ICME)","first-page":"168","article-title":"Body-Part joint detection and association via extended object representation","author":"Zhou","year":"2023"},{"key":"10.1016\/j.asoc.2026.115635_bib0200","series-title":"2024 IEEE International Conference on Image Processing (ICIP)","first-page":"326","article-title":"Crowdassign: a label assignment scheme for pedestrian detection in crowded scenes","author":"Li","year":"2024"},{"key":"10.1016\/j.asoc.2026.115635_bib0205","series-title":"2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"12211","article-title":"Detection in crowded scenes: one proposal, multiple predictions","author":"Chu","year":"2020"},{"key":"10.1016\/j.asoc.2026.115635_bib0210","doi-asserted-by":"crossref","first-page":"24454","DOI":"10.1109\/TITS.2022.3196854","article-title":"Pedestrian detection using MB-CSP model and boosted identity aware non-maximum suppression","volume":"23","author":"Abdelmutalab","year":"2022","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.asoc.2026.115635_bib0215","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.neucom.2020.12.005","article-title":"MAPD: an improved multi-attribute pedestrian detection in a crowd","volume":"432","author":"Wang","year":"2021","journal-title":"Neurocomputing"},{"key":"10.1016\/j.asoc.2026.115635_bib0220","series-title":"2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"6452","article-title":"Adaptive NMS: refining pedestrian detection in a crowd","author":"Liu","year":"2019"},{"key":"10.1016\/j.asoc.2026.115635_bib0225","doi-asserted-by":"crossref","first-page":"3176","DOI":"10.1109\/TIP.2023.3273853","article-title":"OTP-NMS: toward optimal threshold prediction of NMS for crowded pedestrian detection","volume":"32","author":"Tang","year":"2023","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.asoc.2026.115635_bib0230","series-title":"2024 IEEE International Conference on Robotics and Automation (ICRA)","first-page":"4428","article-title":"A safety-adapted loss for pedestrian detection in autonomous driving","author":"Lyssenko","year":"2024"},{"key":"10.1016\/j.asoc.2026.115635_bib0235","doi-asserted-by":"crossref","first-page":"2318","DOI":"10.1109\/LSP.2022.3220147","article-title":"A Coulomb force inspired loss function for high-performance pedestrian detection","volume":"29","author":"Wang","year":"2022","journal-title":"IEEE Signal Process. Lett."},{"key":"10.1016\/j.asoc.2026.115635_bib0240","doi-asserted-by":"crossref","first-page":"12312","DOI":"10.1109\/TITS.2023.3287574","article-title":"Pedestrian detection using multi-scale structure-enhanced super-resolution","volume":"24","author":"Hsu","year":"2023","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.asoc.2026.115635_bib0245","doi-asserted-by":"crossref","first-page":"1125","DOI":"10.1109\/TITS.2019.2963700","article-title":"A part-aware multi-scale fully convolutional network for pedestrian detection","volume":"22","author":"Yang","year":"2021","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.asoc.2026.115635_bib0250","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1109\/TITS.2024.3483892","article-title":"MDFOaNet: a novel multi-modal pedestrian detection network based on multi-scale image dynamic feature optimization and attention mapping","volume":"26","author":"Hao","year":"2025","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.asoc.2026.115635_bib0255","doi-asserted-by":"crossref","DOI":"10.1016\/j.jksuci.2024.102198","article-title":"PFEL-net: a lightweight network to enhance feature for multi-scale pedestrian detection","volume":"36","author":"Tang","year":"2024","journal-title":"J. King Saud Univ. Comput. Inf. Sci."},{"key":"10.1016\/j.asoc.2026.115635_bib0260","series-title":"Proceedings of the European Conference on Computer Vision (ECCV)","article-title":"Learning efficient single-stage pedestrian detectors by asymptotic localization fitting","author":"Liu","year":"2018"},{"key":"10.1016\/j.asoc.2026.115635_bib0265","series-title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI-20","first-page":"509","article-title":"When pedestrian detection meets nighttime surveillance: a new benchmark","author":"Wang","year":"2020"},{"key":"10.1016\/j.asoc.2026.115635_bib0270","series-title":"2020 25th International Conference on Pattern Recognition (ICPR)","first-page":"9180","article-title":"Nighttime pedestrian detection based on feature attention and transformation","author":"Li","year":"2021"},{"key":"10.1016\/j.asoc.2026.115635_bib0275","first-page":"1","article-title":"CTMFNet: CNN and transformer multiscale fusion network of remote sensing urban scene imagery","volume":"61","author":"Song","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.asoc.2026.115635_bib0280","doi-asserted-by":"crossref","first-page":"4732","DOI":"10.3390\/rs15194732","article-title":"A multi-scale convolution and multi-layer fusion network for remote sensing forest tree species recognition","volume":"15","author":"Hou","year":"2023","journal-title":"Remote Sens."},{"key":"10.1016\/j.asoc.2026.115635_bib0285","author":"Li"},{"key":"10.1016\/j.asoc.2026.115635_bib0290","series-title":"2025 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"5678","article-title":"HVI: a new color space for low-light image enhancement","author":"Yan","year":"2025"},{"key":"10.1016\/j.asoc.2026.115635_bib0295","series-title":"2023 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"12470","article-title":"Retinexformer: one-stage retinex-based transformer for low-light image enhancement","author":"Cai","year":"2023"},{"key":"10.1016\/j.asoc.2026.115635_bib0300","series-title":"2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","first-page":"4208","article-title":"Temporally averaged regression for semi-supervised low-light image enhancement","author":"Lee","year":"2023"},{"key":"10.1016\/j.asoc.2026.115635_bib0305","doi-asserted-by":"crossref","first-page":"1229","DOI":"10.1109\/TMM.2023.3278380","article-title":"A semi-supervised underexposed image enhancement network with supervised context attention and multi-exposure fusion","volume":"26","author":"Shi","year":"2024","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.asoc.2026.115635_bib0310","doi-asserted-by":"crossref","first-page":"84231","DOI":"10.1007\/s11042-024-19087-x","article-title":"Low-light DEtection TRansformer (LDETR): object detection in low-light and adverse weather conditions","volume":"83","author":"Tiwari","year":"2024","journal-title":"Multimed. Tools Appl."},{"key":"10.1016\/j.asoc.2026.115635_bib0315","series-title":"2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"5182","article-title":"High-level semantic feature detection: a new perspective for pedestrian detection","author":"Liu","year":"2019"},{"key":"10.1016\/j.asoc.2026.115635_bib0320","series-title":"2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"5385","article-title":"HigherHRNet: scale-aware representation learning for bottom-up human pose estimation","author":"Cheng","year":"2020"},{"key":"10.1016\/j.asoc.2026.115635_bib0325","series-title":"2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.asoc.2026.115635_bib0330","author":"Simonyan"},{"key":"10.1016\/j.asoc.2026.115635_bib0335","series-title":"Proceedings of the IEEE International Conference on Computer Vision","first-page":"764","article-title":"Deformable convolutional networks","author":"Dai","year":"2017"},{"key":"10.1016\/j.asoc.2026.115635_bib0340","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"9308","article-title":"Deformable convnets v2: more deformable, better results","author":"Zhu","year":"2019"},{"key":"10.1016\/j.asoc.2026.115635_bib0345","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110775","article-title":"Application of tswin-F network based on multi-scale feature fusion in tomato leaf lesion recognition","volume":"156","author":"Ye","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.asoc.2026.115635_bib0350","series-title":"Proceedings of the European Conference on Computer Vision (ECCV)","first-page":"734","article-title":"Cornernet: detecting objects as paired keypoints","author":"Law","year":"2018"},{"key":"10.1016\/j.asoc.2026.115635_bib0355","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1109\/TPAMI.2018.2858826","article-title":"Focal loss for dense object detection","volume":"42","author":"Lin","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.asoc.2026.115635_bib0360","series-title":"Advances in Neural Information Processing Systems, 28","article-title":"Faster R-CNN: towards real-time object detection with region proposal networks","author":"Ren","year":"2015"},{"key":"10.1016\/j.asoc.2026.115635_bib0365","doi-asserted-by":"crossref","first-page":"4948","DOI":"10.1109\/TCSVT.2023.3245613","article-title":"CFRLA-net: a context-aware feature representation learning anchor-free network for pedestrian detection","volume":"33","author":"Li","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.asoc.2026.115635_bib0370","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1109\/TPAMI.2011.155","article-title":"Pedestrian detection: an evaluation of the state of the art","volume":"34","author":"Dollar","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.asoc.2026.115635_bib0375","series-title":"2009 IEEE Conference on Computer Vision and Pattern Recognition","first-page":"248","article-title":"ImageNet: a large-scale hierarchical image database","author":"Deng","year":"2009"},{"key":"10.1016\/j.asoc.2026.115635_bib0380","author":"Loshchilov"},{"key":"10.1016\/j.asoc.2026.115635_bib0385","series-title":"2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"11531","article-title":"ECA-net: efficient channel attention for deep convolutional neural networks","author":"Wang","year":"2020"},{"key":"10.1016\/j.asoc.2026.115635_bib0390","series-title":"Proceedings of the European Conference on Computer Vision (ECCV)","article-title":"CBAM: convolutional block attention module","author":"Woo","year":"2018"},{"key":"10.1016\/j.asoc.2026.115635_bib0395","series-title":"2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"13708","article-title":"Coordinate attention for efficient mobile network design","author":"Hou","year":"2021"},{"key":"10.1016\/j.asoc.2026.115635_bib0400","series-title":"Advances in Neural Information Processing Systems, 34","first-page":"22509","article-title":"Speech separation using an asynchronous fully recurrent convolutional neural network","author":"Hu","year":"2021"},{"key":"10.1016\/j.asoc.2026.115635_bib0405","series-title":"2017 IEEE International Conference on Computer Vision (ICCV)","first-page":"4960","article-title":"Illuminating pedestrians via simultaneous detection and segmentation","author":"Brazil","year":"2017"},{"key":"10.1016\/j.asoc.2026.115635_bib0410","series-title":"2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"13427","article-title":"Temporal-context enhanced detection of heavily occluded pedestrians","author":"Wu","year":"2020"},{"key":"10.1016\/j.asoc.2026.115635_bib0415","series-title":"2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"7774","article-title":"Repulsion loss: detecting pedestrians in a crowd","author":"Wang","year":"2018"},{"key":"10.1016\/j.asoc.2026.115635_bib0420","doi-asserted-by":"crossref","first-page":"3143","DOI":"10.1109\/TIP.2019.2957927","article-title":"Taking a look at small-scale pedestrians and occluded pedestrians","volume":"29","author":"Cao","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.asoc.2026.115635_bib0425","first-page":"1","article-title":"Image-level automatic data augmentation for pedestrian detection","volume":"73","author":"Ma","year":"2024","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.asoc.2026.115635_bib0430","series-title":"2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"10747","article-title":"NMS by representative region: towards crowded pedestrian detection by proposal pairing","author":"Huang","year":"2020"},{"key":"10.1016\/j.asoc.2026.115635_bib0435","doi-asserted-by":"crossref","first-page":"27427","DOI":"10.52202\/068431-1989","article-title":"Effectiveness of vision transformer for fast and accurate single-stage pedestrian detection","volume":"35","author":"Yuan","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.asoc.2026.115635_bib0440","series-title":"Proceedings of the 28th ACM International Conference on Multimedia","first-page":"1967","article-title":"NOH-NMS: improving pedestrian detection by nearby objects hallucination","author":"Zhou","year":"2020"},{"key":"10.1016\/j.asoc.2026.115635_bib0445","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.neucom.2022.01.056","article-title":"PRNet++: learning towards generalized occluded pedestrian detection via progressive refinement network","volume":"482","author":"Song","year":"2022","journal-title":"Neurocomputing"},{"key":"10.1016\/j.asoc.2026.115635_bib0450","author":"Yuan"},{"key":"10.1016\/j.asoc.2026.115635_bib0455","first-page":"2154","article-title":"Adaptive pattern-parameter matching for robust pedestrian detection","volume":"35","author":"Liu","year":"2021","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"10.1016\/j.asoc.2026.115635_bib0460","series-title":"2019 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"4966","article-title":"Mask-guided attention network for occluded pedestrian detection","author":"Pang","year":"2019"},{"key":"10.1016\/j.asoc.2026.115635_bib0465","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/j.patrec.2025.01.026","article-title":"OSS-OCL: occlusion scenario simulation and occluded-edge concentrated learning for pedestrian detection","volume":"189","author":"Lu","year":"2025","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.asoc.2026.115635_bib0470","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.neucom.2021.11.091","article-title":"Urban scene based semantical modulation for pedestrian detection","volume":"474","author":"Jiang","year":"2022","journal-title":"Neurocomputing"},{"key":"10.1016\/j.asoc.2026.115635_bib0475","doi-asserted-by":"crossref","unstructured":"J. Xie, H. Cholakkal, R. Anwer, F. Khan, Y. Pang, L. Shao, M. Shah, Count- and similarity-aware R-CNN for pedestrian detection, 2020, 88\u2013104, 10.1007\/978-3-030-58520-4_6","DOI":"10.1007\/978-3-030-58520-4_6"},{"key":"10.1016\/j.asoc.2026.115635_bib0480","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.126613","article-title":"Ms-VLPD: a multi-scale VLPD based method for pedestrian detection","volume":"271","author":"Huang","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.asoc.2026.115635_bib0485","series-title":"2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"15844","article-title":"End-to-end object detection with fully convolutional network","author":"Wang","year":"2021"},{"key":"10.1016\/j.asoc.2026.115635_bib0490","series-title":"2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"3250","article-title":"Optimal proposal learning for deployable end-to-end pedestrian detection","author":"Song","year":"2023"},{"key":"10.1016\/j.asoc.2026.115635_bib0495","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106911","article-title":"RC-DETR: improving DETRs in crowded pedestrian detection via rank-based contrastive learning","volume":"182","author":"Gao","year":"2025","journal-title":"Neural Netw."},{"key":"10.1016\/j.asoc.2026.115635_bib0500","series-title":"2019 IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"9626","article-title":"FCOS: fully convolutional one-stage object detection","author":"Tian","year":"2019"}],"container-title":["Applied Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626010835?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1568494626010835?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T15:48:18Z","timestamp":1784216898000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1568494626010835"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":100,"alternative-id":["S1568494626010835"],"URL":"https:\/\/doi.org\/10.1016\/j.asoc.2026.115635","relation":{},"ISSN":["1568-4946"],"issn-type":[{"value":"1568-4946","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"RIFL-Net: A Retinex-guided illumination-invariant feature learning network for nighttime pedestrian detection","name":"articletitle","label":"Article Title"},{"value":"Applied Soft Computing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.asoc.2026.115635","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"115635"}}