{"total":126,"rows":[{"id":"2211.15654","title":"OpenScene: 3D Scene Understanding with Open Vocabularies","created":"2022-11-28","cited_by_count":559,"area":null},{"id":"2210.03105","title":"Mask3D: Mask Transformer for 3D Semantic Instance Segmentation","created":"2022-10-06","cited_by_count":303,"area":null},{"id":"2306.13631","title":"OpenMask3D: Open-Vocabulary 3D Instance Segmentation","created":"2023-06-23","cited_by_count":289,"area":null},{"id":"2204.07761","title":"Language-Grounded Indoor 3D Semantic Segmentation in the Wild","created":"2022-04-16","cited_by_count":246,"area":null},{"id":"2303.17597","title":"Robo3D: Towards Robust and Reliable 3D Perception against Corruptions","created":"2023-03-30","cited_by_count":129,"area":null},{"id":"2303.05367","title":"Rethinking Range View Representation for LiDAR Segmentation","created":"2023-03-09","cited_by_count":128,"area":"wm"},{"id":"2304.06906","title":"Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene Understanding","created":"2023-04-14","cited_by_count":113,"area":null},{"id":"2305.03045","title":"OctFormer: Octree-based Transformers for 3D Point Clouds","created":"2023-05-04","cited_by_count":109,"area":null},{"id":"2207.00026","title":"LaserMix for Semi-Supervised LiDAR Semantic Segmentation","created":"2022-06-30","cited_by_count":93,"area":null},{"id":"2312.11557","title":"SAI3D: Segment Any Instance in 3D Scenes","created":"2023-12-17","cited_by_count":90,"area":null},{"id":"2207.12824","title":"Compositional Human-Scene Interaction Synthesis with Semantic Control","created":"2022-07-26","cited_by_count":83,"area":null},{"id":"2208.00223","title":"PolarMix: A General Data Augmentation Technique for LiDAR Point Clouds","created":"2022-07-30","cited_by_count":74,"area":null},{"id":"2404.03650","title":"OpenNeRF: Open Set 3D Neural Scene Segmentation with Pixel-Wise Features and Rendered Novel Views","created":"2024-04-04","cited_by_count":69,"area":"mllm"},{"id":"2312.17232","title":"Segment3D: Learning Fine-Grained Class-Agnostic 3D Segmentation without Manual Labels","created":"2023-12-28","cited_by_count":64,"area":null},{"id":"2309.05573","title":"UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebase","created":"2023-09-11","cited_by_count":57,"area":null},{"id":"2203.05272","title":"Contrastive Boundary Learning for Point Cloud Segmentation","created":"2022-03-10","cited_by_count":56,"area":null},{"id":"2303.14191","title":"Masked Scene Contrast: A Scalable Framework for Unsupervised 3D Representation Learning","created":"2023-03-24","cited_by_count":56,"area":null},{"id":"2112.02990","title":"4DContrast: Contrastive Learning with Dynamic Correspondences for 3D Scene Understanding","created":"2021-12-06","cited_by_count":54,"area":null},{"id":"2207.09778","title":"CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation","created":"2022-07-20","cited_by_count":54,"area":null},{"id":"2405.05258","title":"Multi-Modal Data-Efficient 3D Scene Understanding for Autonomous Driving","created":"2024-05-08","cited_by_count":54,"area":null},{"id":"2312.04484","title":"FRNet: Frustum-Range Networks for Scalable LiDAR Segmentation","created":"2023-12-07","cited_by_count":50,"area":null},{"id":"2204.07548","title":"Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation","created":"2022-04-15","cited_by_count":47,"area":null},{"id":"2212.00338","title":"3D-Aware Object Goal Navigation via Simultaneous Exploration and Identification","created":"2022-12-01","cited_by_count":46,"area":null},{"id":"2301.01100","title":"Understanding Imbalanced Semantic Segmentation Through Neural Collapse","created":"2023-01-03","cited_by_count":46,"area":null},{"id":"2111.15242","title":"ConDA: Unsupervised Domain Adaptation for LiDAR Segmentation via Regularized Domain Concatenation","created":"2021-11-30","cited_by_count":41,"area":null},{"id":"2305.16404","title":"GrowSP: Unsupervised Semantic Segmentation of 3D Point Clouds","created":"2023-05-25","cited_by_count":34,"area":null},{"id":"2312.15742","title":"DI-V2X: Learning Domain-Invariant Representation for Vehicle-Infrastructure Collaborative 3D Object Detection","created":"2023-12-25","cited_by_count":34,"area":null},{"id":"2208.02879","title":"PointConvFormer: Revenge of the Point-based Convolution","created":"2022-08-04","cited_by_count":30,"area":null},{"id":"2207.11209","title":"Divide and Conquer: 3D Point Cloud Instance Segmentation With Point-Wise Binarization","created":"2022-07-22","cited_by_count":26,"area":null},{"id":"2405.01538","title":"Multi-Space Alignments Towards Universal LiDAR Segmentation","created":"2024-05-02","cited_by_count":25,"area":null},{"id":"2212.00786","title":"3D Segmentation of Humans in Point Clouds with Synthetic Data","created":"2022-12-01","cited_by_count":24,"area":null},{"id":"2304.01464","title":"Hierarchical Supervision and Shuffle Data Augmentation for 3D Semi-Supervised Object Detection","created":"2023-04-04","cited_by_count":24,"area":"distill"},{"id":"2308.12113","title":"Advancements in Point Cloud Data Augmentation for Deep Learning: A Survey","created":"2023-08-23","cited_by_count":24,"area":null},{"id":"2312.15084","title":"Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning","created":"2023-12-22","cited_by_count":23,"area":null},{"id":"2501.18592","title":"Advances in Multimodal Adaptation and Generalization: From Traditional Approaches to Foundation Models","created":"2025-01-30","cited_by_count":23,"area":null},{"id":"2208.04309","title":"3D Vision with Transformers: A Survey","created":"2022-08-08","cited_by_count":21,"area":null},{"id":"2305.04691","title":"Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey","created":"2023-05-08","cited_by_count":21,"area":null},{"id":"2305.19812","title":"A Survey of Label-Efficient Deep Learning for 3D Point Clouds","created":"2023-05-31","cited_by_count":20,"area":null},{"id":"2308.14619","title":"Compositional Semantic Mix for Domain Adaptation in Point Cloud Segmentation","created":"2023-08-28","cited_by_count":20,"area":null},{"id":"2607.05352","title":"Multiplayer Interactive World Models with Representation Autoencoders","created":"2026-07-06","cited_by_count":19,"area":"wm"},{"id":"2301.00970","title":"Benchmarking the Robustness of LiDAR Semantic Segmentation Models","created":"2023-01-03","cited_by_count":18,"area":null},{"id":"2407.13362","title":"Open Vocabulary 3D Scene Understanding via Geometry Guided Self-Distillation","created":"2024-07-18","cited_by_count":17,"area":"distill"},{"id":"2503.16282","title":"Generalized Few-shot 3D Point Cloud Segmentation with Vision-Language Model","created":"2025-03-20","cited_by_count":17,"area":"mllm"},{"id":"2303.14378","title":"Instant Domain Augmentation for LiDAR Semantic Segmentation","created":"2023-03-25","cited_by_count":16,"area":null},{"id":"2407.09781","title":"Dense Multimodal Alignment for Open-Vocabulary 3D Scene Understanding","created":"2024-07-13","cited_by_count":16,"area":"mllm"},{"id":"2206.12073","title":"MaskRange: A Mask-classification Model for Range-view based LiDAR Segmentation","created":"2022-06-24","cited_by_count":15,"area":null},{"id":"2207.09084","title":"Dual Adaptive Transformations for Weakly Supervised Point Cloud Segmentation","created":"2022-07-19","cited_by_count":15,"area":null},{"id":"2403.10001","title":"Visual Foundation Models Boost Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation","created":"2024-03-15","cited_by_count":15,"area":null},{"id":"2204.05599","title":"HyperDet3D: Learning a Scene-conditioned 3D Object Detector","created":"2022-04-12","cited_by_count":14,"area":null},{"id":"2311.12174","title":"LABELMAKER: Automatic Semantic Label Generation from RGB-D Trajectories","created":"2023-11-20","cited_by_count":14,"area":null},{"id":"2407.02286","title":"Rethinking Data Augmentation for Robust LiDAR Semantic Segmentation in Adverse Weather","created":"2024-07-02","cited_by_count":14,"area":null},{"id":"2204.01599","title":"DODA: Data-oriented Sim-to-Real Domain Adaptation for 3D Semantic Segmentation","created":"2022-04-04","cited_by_count":13,"area":null},{"id":"2304.11705","title":"Walking Your LiDOG: A Journey Through Multiple Domains for LiDAR Semantic Segmentation","created":"2023-04-23","cited_by_count":13,"area":null},{"id":"2305.05026","title":"Self-supervised Pre-training with Masked Shape Prediction for 3D Scene Understanding","created":"2023-05-08","cited_by_count":13,"area":null},{"id":"2503.16707","title":"Cross-Modal and Uncertainty-Aware Agglomeration for Open-Vocabulary 3D Scene Understanding","created":"2025-03-20","cited_by_count":13,"area":"mllm"},{"id":"2304.04248","title":"Curricular Object Manipulation in LiDAR-based Object Detection","created":"2023-04-09","cited_by_count":12,"area":null},{"id":"2205.13490","title":"SemAffiNet: Semantic-Affine Transformation for Point Cloud Segmentation","created":"2022-05-26","cited_by_count":11,"area":null},{"id":"2310.20293","title":"Annotator: A Generic Active Learning Baseline for LiDAR Semantic Segmentation","created":"2023-10-31","cited_by_count":11,"area":null},{"id":"2501.09428","title":"AugRefer: Advancing 3D Visual Grounding via Cross-Modal Augmentation and Spatial Relation-based Referring","created":"2025-01-16","cited_by_count":10,"area":null},{"id":"2210.01558","title":"GaIA: Graphical Information Gain based Attention Network for Weakly Supervised Point Cloud Semantic Segmentation","created":"2022-10-02","cited_by_count":9,"area":null},{"id":"2304.03763","title":"Clutter Detection and Removal in 3D Scenes with View-Consistent Inpainting","created":"2023-04-07","cited_by_count":9,"area":null},{"id":"2408.17027","title":"ConDense: Consistent 2D/3D Pre-training for Dense and Sparse Features from Multi-View Images","created":"2024-08-30","cited_by_count":9,"area":null},{"id":"2212.04668","title":"Synthetic-to-Real Domain Generalized Semantic Segmentation for 3D Indoor Point Clouds","created":"2022-12-09","cited_by_count":8,"area":null},{"id":"2308.13900","title":"Semi-Supervised Semantic Segmentation via Marginal Contextual Information","created":"2023-08-26","cited_by_count":8,"area":null},{"id":"2512.14364","title":"Unified Semantic Transformer for 3D Scene Understanding","created":"2025-12-16","cited_by_count":8,"area":null},{"id":"2202.10705","title":"PointMatch: A Consistency Training Framework for Weakly Supervised Semantic Segmentation of 3D Point Clouds","created":"2022-02-22","cited_by_count":7,"area":null},{"id":"2203.09887","title":"CodedVTR: Codebook-based Sparse Voxel Transformer with Geometric Guidance","created":"2022-03-18","cited_by_count":7,"area":null},{"id":"2305.12853","title":"Real-Aug: Realistic Scene Synthesis for LiDAR Augmentation in 3D Object Detection","created":"2023-05-22","cited_by_count":7,"area":null},{"id":"2311.01989","title":"Leveraging Large-Scale Pretrained Vision Foundation Models for Label-Efficient 3D Point Cloud Segmentation","created":"2023-11-03","cited_by_count":7,"area":null},{"id":"2312.12098","title":"Rethinking LiDAR Domain Generalization: Single Source as Multiple Density Domains","created":"2023-12-19","cited_by_count":7,"area":null},{"id":"2410.13924","title":"ARKit LabelMaker: A New Scale for Indoor 3D Scene Understanding","created":"2024-10-17","cited_by_count":7,"area":null},{"id":"2203.10546","title":"Towards 3D Scene Understanding by Referring Synthetic Models","created":"2022-03-20","cited_by_count":6,"area":null},{"id":"2206.09664","title":"What Can be Seen is What You Get: Structure Aware Point Cloud Augmentation","created":"2022-06-20","cited_by_count":6,"area":null},{"id":"2304.07486","title":"Region-Enhanced Feature Learning for Scene Semantic Segmentation","created":"2023-04-15","cited_by_count":6,"area":null},{"id":"2308.09314","title":"Retro-FPN: Retrospective Feature Pyramid Network for Point Cloud Semantic Segmentation","created":"2023-08-18","cited_by_count":6,"area":null},{"id":"2311.18068","title":"ALSTER: A Local Spatio-Temporal Expert for Online 3D Semantic Reconstruction","created":"2023-11-29","cited_by_count":6,"area":null},{"id":"2312.08009","title":"Semi-Supervised Class-Agnostic Motion Prediction with Pseudo Label Regeneration and BEVMix","created":"2023-12-13","cited_by_count":6,"area":null},{"id":"2402.14215","title":"Swin3D++: Effective Multi-Source Pretraining for 3D Indoor Scene Understanding","created":"2024-02-22","cited_by_count":6,"area":null},{"id":"2503.08512","title":"SAS: Segment Any 3D Scene with Integrated 2D Priors","created":"2025-03-11","cited_by_count":6,"area":null},{"id":"2403.11691","title":"TTT-KD: Test-Time Training for 3D Semantic Segmentation through Knowledge Distillation from Foundation Models","created":"2024-03-18","cited_by_count":5,"area":"distill"},{"id":"2404.07504","title":"Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange","created":"2024-04-11","cited_by_count":5,"area":null},{"id":"2503.12539","title":"BFANet: Revisiting 3D Semantic Segmentation with Boundary Feature Analysis","created":"2025-03-16","cited_by_count":5,"area":null},{"id":"2112.01801","title":"Mesh Convolution with Continuous Filters for 3D Surface Parsing","created":"2021-12-03","cited_by_count":4,"area":null},{"id":"2212.02057","title":"DA-CIL: Towards Domain Adaptive Class-Incremental 3D Object Detection","created":"2022-12-05","cited_by_count":4,"area":null},{"id":"2308.02883","title":"Cross-modal & Cross-domain Learning for Unsupervised LiDAR Semantic Segmentation","created":"2023-08-05","cited_by_count":4,"area":null},{"id":"2308.15479","title":"3D Adversarial Augmentations for Robust Out-of-Domain Predictions","created":"2023-08-29","cited_by_count":4,"area":null},{"id":"2408.10537","title":"Subspace Prototype Guidance for Mitigating Class Imbalance in Point Cloud Semantic Segmentation","created":"2024-08-20","cited_by_count":4,"area":null},{"id":"2604.19609","title":"Volume Transformer: Revisiting Vanilla Transformers for 3D Scene Understanding","created":"2026-04-21","cited_by_count":4,"area":null},{"id":"2210.16810","title":"SL3D: Self-supervised-Self-labeled 3D Recognition","created":"2022-10-30","cited_by_count":3,"area":null},{"id":"2303.09219","title":"MixCycle: Mixup Assisted Semi-Supervised 3D Single Object Tracking with Cycle Consistency","created":"2023-03-16","cited_by_count":3,"area":null},{"id":"2309.16956","title":"Model2Scene: Learning 3D Scene Representation via Contrastive Language-CAD Models Pre-training","created":"2023-09-29","cited_by_count":3,"area":null},{"id":"2412.11540","title":"SP$^2$T: Sparse Proxy Attention for Dual-stream Point Transformer","created":"2024-12-16","cited_by_count":3,"area":null},{"id":"2502.09274","title":"FLARES: Fast and Accurate LiDAR Multi-Range Semantic Segmentation","created":"2025-02-13","cited_by_count":3,"area":null},{"id":"2503.09878","title":"CleverDistiller: Simple and Spatially Consistent Cross-modal Distillation","created":"2025-03-12","cited_by_count":3,"area":null},{"id":"2112.01316","title":"Putting 3D Spatially Sparse Networks on a Diet","created":"2021-12-02","cited_by_count":2,"area":null},{"id":"2212.09517","title":"Fake it, Mix it, Segment it: Bridging the Domain Gap Between Lidar Sensors","created":"2022-12-19","cited_by_count":2,"area":null},{"id":"2305.14038","title":"Why semantics matters: A deep study on semantic particle-filtering localization in a LiDAR semantic pole-map","created":"2023-05-23","cited_by_count":2,"area":null},{"id":"2401.06145","title":"Minuet: Accelerating 3D Sparse Convolutions on GPUs","created":"2023-12-01","cited_by_count":2,"area":null},{"id":"2408.11280","title":"Exploring Scene Affinity for Semi-Supervised LiDAR Semantic Segmentation","created":"2024-08-21","cited_by_count":2,"area":null},{"id":"2111.08434","title":"Robust 3D Scene Segmentation through Hierarchical and Learnable Part-Fusion","created":"2021-11-16","cited_by_count":1,"area":null}],"next_cursor":"100"}