{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T05:57:24Z","timestamp":1777874244819,"version":"3.51.4"},"reference-count":77,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.neucom.2026.133634","type":"journal-article","created":{"date-parts":[[2026,4,12]],"date-time":"2026-04-12T16:30:54Z","timestamp":1776011454000},"page":"133634","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Instance-aware adaptive label assignment for 3D object detection"],"prefix":"10.1016","volume":"685","author":[{"given":"Jianping","family":"Zhong","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1872-5424","authenticated-orcid":false,"given":"Xianzhu","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Qinglin","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Feng","family":"Jiang","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.neucom.2026.133634_bib0005","doi-asserted-by":"crossref","first-page":"10949","DOI":"10.1109\/TPAMI.2025.3594749","article-title":"Parameter-efficient fine-tuning in spectral domain for point cloud learning","volume":"47","author":"Liang","year":"2025","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.133634_bib0010","series-title":"IEEE International Conference on Multimedia and Expo","first-page":"1","article-title":"Geometric-aware mapping and uncertainty modeling for semantic scene completion","author":"Liu","year":"2025"},{"key":"10.1016\/j.neucom.2026.133634_bib0015","author":"Tang"},{"key":"10.1016\/j.neucom.2026.133634_bib0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.129916","article-title":"DSQN: robust path planning of mobile robot based on deep spiking q-network","volume":"634","author":"Kumar","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2026.133634_bib0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.129622","article-title":"Comparing synchronous and asynchronous UWB time-based localization systems for autonomous mobile robots","volume":"629","author":"Ferrero-Guill\u00e9n","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2026.133634_bib0030","doi-asserted-by":"crossref","first-page":"2425","DOI":"10.1007\/s11263-023-01820-y","article-title":"Learning geometric transformation for point cloud completion","volume":"131","author":"Zhang","year":"2023","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.neucom.2026.133634_bib0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.129841","article-title":"Ragnet3D: learning distinguishable representation for pooled grids in 3D object detection","volume":"635","author":"Chen","year":"2025","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2026.133634_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.127807","article-title":"Ariou: anchor-free rotation-decoupling iou-based optimization for 3D object detection","volume":"594","author":"Wen","year":"2024","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2026.133634_bib0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.127814","article-title":"Srfdet3D: sparse region fusion based 3D object detection","volume":"593","author":"Erabati","year":"2024","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2026.133634_bib0050","doi-asserted-by":"crossref","first-page":"1306","DOI":"10.1007\/s11263-024-02244-y","article-title":"2D semantic-guided semantic scene completion","volume":"133","author":"Liu","year":"2025","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.neucom.2026.133634_bib0055","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.neucom.2013.05.065","article-title":"3D scene reconstruction enhancement method based on automatic context analysis and convex optimization","volume":"137","author":"Le","year":"2014","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2026.133634_bib0060","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"5613","article-title":"Multi-view consistent 3D panoptic scene understanding","author":"Liu","year":"2025"},{"key":"10.1016\/j.neucom.2026.133634_bib0065","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"15321","article-title":"Hinted: hard instance enhanced detector with mixed-density feature fusion for sparsely-supervised 3D object detection","author":"Xia","year":"2024"},{"key":"10.1016\/j.neucom.2026.133634_bib0070","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"5652","article-title":"Efficient deformable convnets: rethinking dynamic and sparse operator for vision applications","author":"Xiong","year":"2024"},{"key":"10.1016\/j.neucom.2026.133634_bib0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.108868","article-title":"Dsla: dynamic smooth label assignment for efficient anchor-free object detection","volume":"131","author":"Su","year":"2022","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.neucom.2026.133634_bib0080","doi-asserted-by":"crossref","first-page":"10134","DOI":"10.1109\/TCSVT.2025.3563083","article-title":"Dynamic learnable label assignment for indoor 3D object detection","volume":"35","author":"Liu","year":"2025","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.neucom.2026.133634_bib0085","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"11040","article-title":"3Dssd: point-based 3D single stage object detector","author":"Yang","year":"2020"},{"key":"10.1016\/j.neucom.2026.133634_bib0090","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"221","article-title":"Sasa: semantics-augmented set abstraction for point-based 3D object detection","volume":"vol. 36","author":"Chen","year":"2022"},{"key":"10.1016\/j.neucom.2026.133634_bib0095","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"18953","article-title":"Not all points are equal: learning highly efficient point-based detectors for 3D lidar point clouds","author":"Zhang","year":"2022"},{"key":"10.1016\/j.neucom.2026.133634_bib0100","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"770","article-title":"Pointrcnn: 3D object proposal generation and detection from point cloud","author":"Shi","year":"2019"},{"key":"10.1016\/j.neucom.2026.133634_bib0105","series-title":"2012 IEEE Conference on Computer Vision and Pattern Recognition","first-page":"3354","article-title":"Are we ready for autonomous driving? The kitti vision benchmark suite","author":"Geiger","year":"2012"},{"key":"10.1016\/j.neucom.2026.133634_bib0110","series-title":"2021 IEEE\/CVF International Conference on Computer Vision","first-page":"3490","article-title":"Tood: task-aligned one-stage object detection","author":"Feng","year":"2021"},{"key":"10.1016\/j.neucom.2026.133634_bib0115","doi-asserted-by":"crossref","first-page":"3096","DOI":"10.1109\/TPAMI.2021.3050494","article-title":"Learning to match anchors for visual object detection","volume":"44","author":"Zhang","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.133634_bib0120","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"11621","article-title":"Nuscenes: a multimodal dataset for autonomous driving","author":"Caesar","year":"2020"},{"key":"10.1016\/j.neucom.2026.133634_bib0125","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"4604","article-title":"Pointpainting: sequential fusion for 3D object detection","author":"Vora","year":"2020"},{"key":"10.1016\/j.neucom.2026.133634_bib0130","doi-asserted-by":"crossref","first-page":"2218","DOI":"10.1109\/TCSVT.2025.3612592","article-title":"Ascformer: an adaptive strucure-aware cascaded transformer for 3D object detection","volume":"36","author":"Zhang","year":"2025","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.neucom.2026.133634_bib0135","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"26879","article-title":"Geoformer: geometry point encoder for 3D object detection with graph-based transformer","author":"Jin","year":"2025"},{"key":"10.1016\/j.neucom.2026.133634_bib0140","doi-asserted-by":"crossref","first-page":"6324","DOI":"10.1109\/TCSVT.2022.3167114","article-title":"Decoupled r-cnn: sensitivity-specific detector for higher accurate localization","volume":"32","author":"Wang","year":"2022","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.neucom.2026.133634_bib0145","doi-asserted-by":"crossref","first-page":"4940","DOI":"10.1109\/TCSVT.2021.3138743","article-title":"Bicsnet: a bidirectional cross-scale backbone for recognition and localization","volume":"32","author":"Peng","year":"2021","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.neucom.2026.133634_bib0150","doi-asserted-by":"crossref","first-page":"1639","DOI":"10.1109\/TCSVT.2019.2906246","article-title":"Detecting small objects using a channel-aware deconvolutional network","volume":"30","author":"Duan","year":"2019","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.neucom.2026.133634_bib0155","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"4490","article-title":"Voxelnet: end-to-end learning for point cloud based 3D object detection","author":"Zhou","year":"2018"},{"key":"10.1016\/j.neucom.2026.133634_bib0160","doi-asserted-by":"crossref","first-page":"3337","DOI":"10.3390\/s18103337","article-title":"Second: sparsely embedded convolutional detection","volume":"18","author":"Yan","year":"2018","journal-title":"Sensors"},{"key":"10.1016\/j.neucom.2026.133634_bib0165","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1109\/LSP.2024.3503359","article-title":"Geometry-guided point generation for 3D object detection","volume":"32","author":"Wang","year":"2024","journal-title":"IEEE Signal Process. Lett."},{"key":"10.1016\/j.neucom.2026.133634_bib0170","doi-asserted-by":"crossref","DOI":"10.1016\/j.displa.2022.102322","article-title":"Deformable pyramid r-cnn for 3D object detection (chinamm2022)","volume":"75","author":"Hou","year":"2022","journal-title":"Displays"},{"key":"10.1016\/j.neucom.2026.133634_bib0175","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"12697","article-title":"Pointpillars: fast encoders for object detection from point clouds","author":"Lang","year":"2019"},{"key":"10.1016\/j.neucom.2026.133634_bib0180","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"2271","article-title":"Jpv-net: joint point-voxel representations for accurate 3D object detection","volume":"vol. 36","author":"Song","year":"2022"},{"key":"10.1016\/j.neucom.2026.133634_bib0185","doi-asserted-by":"crossref","first-page":"5252","DOI":"10.1109\/TCSVT.2022.3140248","article-title":"Convex-hull feature adaptation for oriented and densely packed object detection","volume":"32","author":"Guo","year":"2022","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.neucom.2026.133634_bib0190","doi-asserted-by":"crossref","first-page":"7869","DOI":"10.1109\/TCSVT.2022.3186070","article-title":"Rsdet++: point-based modulated loss for more accurate rotated object detection","volume":"32","author":"Qian","year":"2022","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.neucom.2026.133634_bib0195","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"1201","article-title":"Voxel r-cnn: towards high performance voxel-based 3D object detection","volume":"vol. 35","author":"Deng","year":"2021"},{"key":"10.1016\/j.neucom.2026.133634_bib0200","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"21674","article-title":"Voxelnext: fully sparse voxelnet for 3D object detection and tracking","author":"Chen","year":"2023"},{"key":"10.1016\/j.neucom.2026.133634_bib0205","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"652","article-title":"Pointnet: deep learning on point sets for 3D classification and segmentation","author":"Qi","year":"2017"},{"key":"10.1016\/j.neucom.2026.133634_bib0210","series-title":"Advances in Neural Information Processing Systems","article-title":"Pointnet++: deep hierarchical feature learning on point sets in a metric space","author":"Qi","year":"2017"},{"key":"10.1016\/j.neucom.2026.133634_bib0215","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"7463","article-title":"3D object detection with pointformer","author":"Pan","year":"2021"},{"key":"10.1016\/j.neucom.2026.133634_bib0220","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"10529","article-title":"Pv-rcnn: point-voxel feature set abstraction for 3D object detection","author":"Shi","year":"2020"},{"key":"10.1016\/j.neucom.2026.133634_bib0225","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1007\/s11263-022-01710-9","article-title":"Pv-rcnn++: point-voxel feature set abstraction with local vector representation for 3D object detection","volume":"131","author":"Shi","year":"2023","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.neucom.2026.133634_bib0230","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"9775","article-title":"Fast point r-cnn","author":"Chen","year":"2019"},{"key":"10.1016\/j.neucom.2026.133634_bib0235","series-title":"Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision","first-page":"772","article-title":"M3Detr: multi-representation, multi-scale, mutual-relation 3D object detection with transformers","author":"Guan","year":"2022"},{"key":"10.1016\/j.neucom.2026.133634_bib0240","author":"Zhang"},{"key":"10.1016\/j.neucom.2026.133634_bib0245","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"8514","article-title":"Varifocalnet: an iou-aware dense object detector","author":"Zhang","year":"2021"},{"key":"10.1016\/j.neucom.2026.133634_bib0250","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"9759","article-title":"Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection","author":"Zhang","year":"2020"},{"key":"10.1016\/j.neucom.2026.133634_bib0255","series-title":"European Conference on Computer Vision","first-page":"355","article-title":"Probabilistic anchor assignment with IOU prediction for object detection","author":"Kim","year":"2020"},{"key":"10.1016\/j.neucom.2026.133634_bib0260","author":"Mao"},{"key":"10.1016\/j.neucom.2026.133634_bib0265","series-title":"Proceedings of the European Conference on Computer Vision","first-page":"720","article-title":"3D-cvf: generating joint camera and lidar features using cross-view spatial feature fusion for 3D object detection","author":"Yoo","year":"2020"},{"key":"10.1016\/j.neucom.2026.133634_bib0270","series-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems","first-page":"10386","article-title":"Clocs: camera-lidar object candidates fusion for 3D object detection","author":"Pang","year":"2020"},{"key":"10.1016\/j.neucom.2026.133634_bib0275","series-title":"Proceedings of the European Conference on Computer Vision","first-page":"35","article-title":"Epnet: enhancing point features with image semantics for 3D object detection","author":"Huang","year":"2020"},{"key":"10.1016\/j.neucom.2026.133634_bib0280","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","first-page":"1907","article-title":"Multi-view 3D object detection network for autonomous driving","author":"Chen","year":"2017"},{"key":"10.1016\/j.neucom.2026.133634_bib0285","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"9403","article-title":"Gd-MAE: generative decoder for MAE pre-training on lidar point clouds","author":"Yang","year":"2023"},{"key":"10.1016\/j.neucom.2026.133634_bib0290","first-page":"1","article-title":"Cmae-3D: contrastive masked autoencoders for self-supervised 3D object detection","author":"Zhang","year":"2024","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.neucom.2026.133634_bib0295","first-page":"1","article-title":"Fuzzy-NMS: improving 3D object detection with fuzzy classification in NMS","author":"Wang","year":"2024","journal-title":"IEEE Trans. Intell. Veh."},{"key":"10.1016\/j.neucom.2026.133634_bib0300","series-title":"Asian Conference on Computer Vision","first-page":"211","article-title":"Sesame: simple, easy 3D object detection with point-wise semantics","author":"Hayeon","year":"2024"},{"key":"10.1016\/j.neucom.2026.133634_bib0305","first-page":"13601","article-title":"Lion: linear group RNN for 3D object detection in point clouds","volume":"37","author":"Liu","year":"2025","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.133634_bib0310","series-title":"International Conference on Image Processing, Computer Vision and Machine Learning","first-page":"1105","article-title":"Enhancing 3D detection accuracy in autonomous driving through pseudo-lidar augmentation and downsampling","author":"Gong","year":"2024"},{"key":"10.1016\/j.neucom.2026.133634_bib0315","doi-asserted-by":"crossref","first-page":"6587","DOI":"10.1109\/TITS.2025.3535595","article-title":"Boosting 3D object detection via self-distilling introspective data","volume":"26","author":"Wang","year":"2025","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"10.1016\/j.neucom.2026.133634_bib0320","doi-asserted-by":"crossref","first-page":"4167","DOI":"10.1109\/TMM.2025.3535289","article-title":"Rafdet: range view augmented fusion network for point-based 3D object detection","volume":"27","author":"Zheng","year":"2025","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.neucom.2026.133634_bib0325","doi-asserted-by":"crossref","DOI":"10.1016\/j.dsp.2025.105171","article-title":"Instance-aware sampling and voxel-transformer encoding for single-stage 3D object detection","volume":"162","author":"Wang","year":"2025","journal-title":"Digit. Signal Process."},{"key":"10.1016\/j.neucom.2026.133634_bib0330","doi-asserted-by":"crossref","first-page":"3436","DOI":"10.1109\/TETCI.2024.3389710","article-title":"Pv-ssd: a multi-modal point cloud 3D object detector based on projection features and voxel features","volume":"8","author":"Shao","year":"2024","journal-title":"IEEE Trans. Emerg. Top. Comput. Intell."},{"key":"10.1016\/j.neucom.2026.133634_bib0335","doi-asserted-by":"crossref","first-page":"4969","DOI":"10.1109\/JSEN.2023.3347575","article-title":"3-d object detection with balanced prediction based on contrastive point loss","volume":"24","author":"Tong","year":"2024","journal-title":"IEEE Sens. J."},{"key":"10.1016\/j.neucom.2026.133634_bib0340","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.122716","article-title":"Mmaf-net: multi-view multi-stage adaptive fusion for multi-sensor 3D object detection","volume":"242","author":"Zhang","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.neucom.2026.133634_bib0345","doi-asserted-by":"crossref","first-page":"3736","DOI":"10.1109\/TPAMI.2023.3345880","article-title":"Mssvt++: mixed-scale sparse voxel transformer with center voting for 3D object detection","volume":"46","author":"Li","year":"2024","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.133634_bib0350","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"1951","article-title":"Std: sparse-to-dense 3D object detector for point cloud","author":"Yang","year":"2019"},{"key":"10.1016\/j.neucom.2026.133634_bib0355","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"14605","article-title":"Hvpr: hybrid voxel-point representation for single-stage 3D object detection","author":"Noh","year":"2021"},{"key":"10.1016\/j.neucom.2026.133634_bib0360","series-title":"IEEE International Conference on Robotics and Automation","first-page":"13408","article-title":"Vic-net: voxelization information compensation network for point cloud 3D object detection","author":"Jiang","year":"2021"},{"key":"10.1016\/j.neucom.2026.133634_bib0365","series-title":"International Conference on 3D Vision","first-page":"85","article-title":"IOU loss for 2D\/3D object detection","author":"Zhou","year":"2019"},{"key":"10.1016\/j.neucom.2026.133634_bib0370","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"11677","article-title":"Tanet: robust 3D object detection from point clouds with triple attention","volume":"vol. 34","author":"Liu","year":"2020"},{"key":"10.1016\/j.neucom.2026.133634_bib0375","author":"Zhang"},{"key":"10.1016\/j.neucom.2026.133634_bib0380","series-title":"Proceedings of the International Conference on Pattern Recognition","first-page":"850","article-title":"Efficient non-maximum suppression","author":"Neubeck","year":"2006"},{"key":"10.1016\/j.neucom.2026.133634_bib0385","author":"Zhao"}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226010313?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226010313?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T19:24:20Z","timestamp":1777577060000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231226010313"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":77,"alternative-id":["S0925231226010313"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2026.133634","relation":{},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Instance-aware adaptive label assignment for 3D object detection","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2026.133634","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":"133634"}}