{"list":"other","total":62,"rows":[{"id":"2304.02643","title":"Segment Anything","created":"2023-04-05","cited_by_count":8234},{"id":"1612.00593","title":"PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation","created":"2016-12-02","cited_by_count":5248},{"id":"1903.11027","title":"nuScenes: A multimodal dataset for autonomous driving","created":"2019-03-26","cited_by_count":4523},{"id":"1706.02413","title":"PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space","created":"2017-06-07","cited_by_count":4401},{"id":"1812.05784","title":"PointPillars: Fast Encoders for Object Detection from Point Clouds","created":"2018-12-14","cited_by_count":1715},{"id":"2011.00931","title":"Point Transformer","created":"2020-11-02","cited_by_count":1470},{"id":"1904.08755","title":"4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks","created":"2019-04-18","cited_by_count":1208},{"id":"1904.08889","title":"KPConv: Flexible and Deformable Convolution for Point Clouds","created":"2019-04-18","cited_by_count":1205},{"id":"1711.10275","title":"3D Semantic Segmentation with Submanifold Sparse Convolutional Networks","created":"2017-11-28","cited_by_count":748},{"id":"1811.12833","title":"ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation","created":"2018-11-30","cited_by_count":623},{"id":"2312.10035","title":"Point Transformer V3: Simpler, Faster, Stronger","created":"2023-12-15","cited_by_count":589},{"id":"1911.11236","title":"RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds","created":"2019-11-25","cited_by_count":585},{"id":"1505.00880","title":"Multi-view Convolutional Neural Networks for 3D Shape Recognition","created":"2015-05-05","cited_by_count":565},{"id":"1912.12033","title":"Deep Learning for 3D Point Clouds: A Survey","created":"2019-12-27","cited_by_count":558},{"id":"2007.16100","title":"Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution","created":"2020-07-31","cited_by_count":423},{"id":"2011.10033","title":"Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation","created":"2020-11-19","cited_by_count":389},{"id":"2210.05666","title":"Point Transformer V2: Grouped Vector Attention and Partition-based Pooling","created":"2022-10-11","cited_by_count":388},{"id":"1902.06326","title":"PIXOR: Real-time 3D Object Detection from Point Clouds","created":"2019-02-17","cited_by_count":358},{"id":"2004.01658","title":"PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation","created":"2020-04-03","cited_by_count":321},{"id":"1904.10620","title":"Bidirectional Learning for Domain Adaptation of Semantic Segmentation","created":"2019-04-24","cited_by_count":308},{"id":"2003.14032","title":"PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation","created":"2020-03-31","cited_by_count":275},{"id":"2012.10992","title":"Deep Continuous Fusion for Multi-Sensor 3D Object Detection","created":"2020-12-20","cited_by_count":263},{"id":"1809.08495","title":"SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud","created":"2018-09-22","cited_by_count":228},{"id":"2003.03653","title":"SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving","created":"2020-03-07","cited_by_count":226},{"id":"1812.07003","title":"3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans","created":"2018-12-17","cited_by_count":217},{"id":"2103.12978","title":"RPVNet: A Deep and Efficient Range-Point-Voxel Fusion Network for LiDAR Point Cloud Segmentation","created":"2021-03-24","cited_by_count":173},{"id":"2207.04397","title":"2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds","created":"2022-07-10","cited_by_count":158},{"id":"2011.13244","title":"MVTN: Multi-View Transformation Network for 3D Shape Recognition","created":"2020-11-26","cited_by_count":140},{"id":"1911.12676","title":"xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation","created":"2019-11-28","cited_by_count":129},{"id":"2303.12766","title":"Spherical Transformer for LiDAR-based 3D Recognition","created":"2023-03-22","cited_by_count":125},{"id":"2304.06906","title":"Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene Understanding","created":"2023-04-14","cited_by_count":113},{"id":"2008.01550","title":"Cylinder3D: An Effective 3D Framework for Driving-scene LiDAR Semantic Segmentation","created":"2020-08-04","cited_by_count":112},{"id":"1511.02300","title":"Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images","created":"2015-11-07","cited_by_count":111},{"id":"2103.14962","title":"Panoptic-PolarNet: Proposal-free LiDAR Point Cloud Panoptic Segmentation","created":"2021-03-27","cited_by_count":107},{"id":"2311.14405","title":"OneFormer3D: One Transformer for Unified Point Cloud Segmentation","created":"2023-11-24","cited_by_count":95},{"id":"2301.10222","title":"RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Driving","created":"2023-01-24","cited_by_count":76},{"id":"2209.09385","title":"LidarMultiNet: Towards a Unified Multi-Task Network for LiDAR Perception","created":"2022-09-19","cited_by_count":74},{"id":"1711.10288","title":"Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation","created":"2017-11-28","cited_by_count":71},{"id":"2303.08600","title":"MSeg3D: Multi-modal 3D Semantic Segmentation for Autonomous Driving","created":"2023-03-15","cited_by_count":68},{"id":"2110.11325","title":"Learning 3D Semantic Segmentation with only 2D Image Supervision","created":"2021-10-21","cited_by_count":60},{"id":"2309.05573","title":"UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebase","created":"2023-09-11","cited_by_count":57},{"id":"2107.14724","title":"Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Semantic Segmentation","created":"2021-07-30","cited_by_count":46},{"id":"2101.07253","title":"Cross-modal Learning for Domain Adaptation in 3D Semantic Segmentation","created":"2021-01-18","cited_by_count":40},{"id":"2503.01210","title":"Every SAM Drop Counts: Embracing Semantic Priors for Multi-Modality Image Fusion and Beyond","created":"2025-03-03","cited_by_count":35},{"id":"2503.14029","title":"Rethinking End-to-End 2D to 3D Scene Segmentation in Gaussian Splatting","created":"2025-03-18","cited_by_count":31},{"id":"2107.14391","title":"From Multi-View to Hollow-3D: Hallucinated Hollow-3D R-CNN for 3D Object Detection","created":"2021-07-30","cited_by_count":24},{"id":"2411.16308","title":"An End-to-End Robust Point Cloud Semantic Segmentation Network with Single-Step Conditional Diffusion Models","created":"2024-11-25","cited_by_count":23},{"id":"2410.22489","title":"Multimodality Helps Few-shot 3D Point Cloud Semantic Segmentation","created":"2024-10-29","cited_by_count":20},{"id":"2309.11839","title":"MoPA: Multi-Modal Prior Aided Domain Adaptation for 3D Semantic Segmentation","created":"2023-09-21","cited_by_count":17},{"id":"2411.14723","title":"Effective SAM Combination for Open-Vocabulary Semantic Segmentation","created":"2024-11-22","cited_by_count":17},{"id":"2503.16282","title":"Generalized Few-shot 3D Point Cloud Segmentation with Vision-Language Model","created":"2025-03-20","cited_by_count":17},{"id":"2304.02991","title":"Exploiting the Complementarity of 2D and 3D Networks to Address Domain-Shift in 3D Semantic Segmentation","created":"2023-04-06","cited_by_count":14},{"id":"2308.13323","title":"SVQNet: Sparse Voxel-Adjacent Query Network for 4D Spatio-Temporal LiDAR Semantic Segmentation","created":"2023-08-25","cited_by_count":14},{"id":"2311.01556","title":"MemorySeg: Online LiDAR Semantic Segmentation with a Latent Memory","created":"2023-11-02","cited_by_count":14},{"id":"2407.09751","title":"TASeg: Temporal Aggregation Network for LiDAR Semantic Segmentation","created":"2024-07-13","cited_by_count":13},{"id":"2303.12194","title":"LiDARFormer: A Unified Transformer-based Multi-task Network for LiDAR Perception","created":"2023-03-21","cited_by_count":11},{"id":"2307.04231","title":"Mx2M: Masked Cross-Modality Modeling in Domain Adaptation for 3D Semantic Segmentation","created":"2023-07-09","cited_by_count":10},{"id":"2307.04091","title":"CMDFusion: Bidirectional Fusion Network with Cross-modality Knowledge Distillation for LIDAR Semantic Segmentation","created":"2023-07-09","cited_by_count":6},{"id":"2311.17491","title":"Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation","created":"2023-11-29","cited_by_count":6},{"id":"2402.14215","title":"Swin3D++: Effective Multi-Source Pretraining for 3D Indoor Scene Understanding","created":"2024-02-22","cited_by_count":6},{"id":"2503.12539","title":"BFANet: Revisiting 3D Semantic Segmentation with Boundary Feature Analysis","created":"2025-03-16","cited_by_count":5},{"id":"2410.19446","title":"Fusion-then-Distillation: Toward Cross-modal Positive Distillation for Domain Adaptive 3D Semantic Segmentation","created":"2024-10-25","cited_by_count":4}],"next_cursor":null}