{"total":139,"rows":[{"id":"2109.08141","title":"An End-to-End Transformer Model for 3D Object Detection","created":"2021-09-16","cited_by_count":329,"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":"2101.02691","title":"Self-Supervised Pretraining of 3D Features on any Point-Cloud","created":"2021-01-07","cited_by_count":217,"area":null},{"id":"2104.00678","title":"Group-Free 3D Object Detection via Transformers","created":"2021-04-01","cited_by_count":215,"area":null},{"id":"2203.01509","title":"SoftGroup for 3D Instance Segmentation on Point Clouds","created":"2022-03-03","cited_by_count":200,"area":null},{"id":"2103.14898","title":"SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences","created":"2021-03-27","cited_by_count":163,"area":null},{"id":"2204.08721","title":"Multimodal Token Fusion for Vision Transformers","created":"2022-04-19","cited_by_count":136,"area":null},{"id":"2108.02350","title":"Hierarchical Aggregation for 3D Instance Segmentation","created":"2021-08-05","cited_by_count":127,"area":null},{"id":"2110.02210","title":"Mix3D: Out-of-Context Data Augmentation for 3D Scenes","created":"2021-10-05","cited_by_count":126,"area":null},{"id":"2211.15766","title":"Superpoint Transformer for 3D Scene Instance Segmentation","created":"2022-11-28","cited_by_count":116,"area":null},{"id":"2108.07478","title":"Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks","created":"2021-08-17","cited_by_count":99,"area":null},{"id":"2112.00322","title":"FCAF3D: Fully Convolutional Anchor-Free 3D Object Detection","created":"2021-12-01","cited_by_count":97,"area":null},{"id":"2303.15380","title":"Hi4D: 4D Instance Segmentation of Close Human Interaction","created":"2023-03-27","cited_by_count":87,"area":null},{"id":"2301.10222","title":"RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Driving","created":"2023-01-24","cited_by_count":76,"area":null},{"id":"2111.02444","title":"Panoptic 3D Scene Reconstruction From a Single RGB Image","created":"2021-11-03","cited_by_count":70,"area":null},{"id":"2212.00836","title":"UniT3D: A Unified Transformer for 3D Dense Captioning and Visual Grounding","created":"2022-12-01","cited_by_count":69,"area":null},{"id":"2104.06114","title":"Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds","created":"2021-04-13","cited_by_count":67,"area":null},{"id":"2102.12472","title":"4D Panoptic LiDAR Segmentation","created":"2021-02-24","cited_by_count":65,"area":null},{"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":"2104.11225","title":"Pri3D: Can 3D Priors Help 2D Representation Learning?","created":"2021-04-22","cited_by_count":61,"area":null},{"id":"2210.04264","title":"CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds","created":"2022-10-09","cited_by_count":58,"area":null},{"id":"2109.05441","title":"Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR-based Perception","created":"2021-09-12","cited_by_count":57,"area":null},{"id":"2306.08045","title":"Efficient 3D Semantic Segmentation with Superpoint Transformer","created":"2023-06-13","cited_by_count":57,"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":"2503.19199","title":"Open-Vocabulary Functional 3D Scene Graphs for Real-World Indoor Spaces","created":"2025-03-24","cited_by_count":54,"area":null},{"id":"2303.00246","title":"ISBNet: a 3D Point Cloud Instance Segmentation Network with Instance-aware Sampling and Box-aware Dynamic Convolution","created":"2023-03-01","cited_by_count":53,"area":null},{"id":"2307.14620","title":"NeRF-Det: Learning Geometry-Aware Volumetric Representation for Multi-View 3D Object Detection","created":"2023-07-27","cited_by_count":51,"area":null},{"id":"2201.00785","title":"Implicit Autoencoder for Point-Cloud Self-Supervised Representation Learning","created":"2022-01-03","cited_by_count":46,"area":null},{"id":"2309.01692","title":"Mask-Attention-Free Transformer for 3D Instance Segmentation","created":"2023-09-04","cited_by_count":46,"area":null},{"id":"2204.02251","title":"RBGNet: Ray-based Grouping for 3D Object Detection","created":"2022-04-05","cited_by_count":40,"area":null},{"id":"2207.07372","title":"3D Instances as 1D Kernels","created":"2022-07-15","cited_by_count":36,"area":null},{"id":"2308.16632","title":"3D-STMN: Dependency-Driven Superpoint-Text Matching Network for End-to-End 3D Referring Expression Segmentation","created":"2023-08-31","cited_by_count":36,"area":null},{"id":"2209.14858","title":"4D-StOP: Panoptic Segmentation of 4D LiDAR using Spatio-temporal Object Proposal Generation and Aggregation","created":"2022-09-29","cited_by_count":35,"area":null},{"id":"2308.04409","title":"V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection","created":"2023-08-08","cited_by_count":35,"area":null},{"id":"2312.08372","title":"SAM-guided Graph Cut for 3D Instance Segmentation","created":"2023-12-13","cited_by_count":35,"area":null},{"id":"2108.07511","title":"LIF-Seg: LiDAR and Camera Image Fusion for 3D LiDAR Semantic Segmentation","created":"2021-08-17","cited_by_count":34,"area":null},{"id":"2306.00977","title":"AGILE3D: Attention Guided Interactive Multi-object 3D Segmentation","created":"2023-06-01","cited_by_count":33,"area":null},{"id":"2302.02871","title":"Top-Down Beats Bottom-Up in 3D Instance Segmentation","created":"2023-02-06","cited_by_count":31,"area":null},{"id":"2409.18431","title":"Search3D: Hierarchical Open-Vocabulary 3D Segmentation","created":"2024-09-27","cited_by_count":31,"area":null},{"id":"2103.05423","title":"Deep Learning Based 3D Segmentation: A Survey","created":"2021-03-09","cited_by_count":30,"area":null},{"id":"2203.14662","title":"MaskGroup: Hierarchical Point Grouping and Masking for 3D Instance Segmentation","created":"2022-03-28","cited_by_count":30,"area":null},{"id":"2406.02548","title":"Open-YOLO 3D: Towards Fast and Accurate Open-Vocabulary 3D Instance Segmentation","created":"2024-06-04","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":"2212.00786","title":"3D Segmentation of Humans in Point Clouds with Synthetic Data","created":"2022-12-01","cited_by_count":24,"area":null},{"id":"2305.02627","title":"UrbanBIS: a Large-scale Benchmark for Fine-grained Urban Building Instance Segmentation","created":"2023-05-04","cited_by_count":24,"area":null},{"id":"2309.16133","title":"Mask4Former: Mask Transformer for 4D Panoptic Segmentation","created":"2023-09-28","cited_by_count":24,"area":null},{"id":"2204.07183","title":"Interactive Object Segmentation in 3D Point Clouds","created":"2022-04-14","cited_by_count":23,"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":"2201.05972","title":"Sparse Cross-scale Attention Network for Efficient LiDAR Panoptic Segmentation","created":"2022-01-16","cited_by_count":22,"area":null},{"id":"2210.11472","title":"VIBUS: Data-efficient 3D Scene Parsing with VIewpoint Bottleneck and Uncertainty-Spectrum Modeling","created":"2022-10-20","cited_by_count":21,"area":null},{"id":"2203.16832","title":"Point Scene Understanding via Disentangled Instance Mesh Reconstruction","created":"2022-03-31","cited_by_count":20,"area":null},{"id":"2210.01391","title":"Bridged Transformer for Vision and Point Cloud 3D Object Detection","created":"2022-10-04","cited_by_count":20,"area":null},{"id":"2409.04234","title":"UniDet3D: Multi-dataset Indoor 3D Object Detection","created":"2024-09-06","cited_by_count":20,"area":null},{"id":"2108.11771","title":"ICM-3D: Instantiated Category Modeling for 3D Instance Segmentation","created":"2021-08-26","cited_by_count":18,"area":null},{"id":"2303.13509","title":"Position-Guided Point Cloud Panoptic Segmentation Transformer","created":"2023-03-23","cited_by_count":17,"area":null},{"id":"2307.14392","title":"Human-centric Scene Understanding for 3D Large-scale Scenarios","created":"2023-07-26","cited_by_count":17,"area":null},{"id":"2204.11402","title":"PointInst3D: Segmenting 3D Instances by Points","created":"2022-04-25","cited_by_count":16,"area":null},{"id":"2111.15210","title":"Point Cloud Instance Segmentation with Semi-supervised Bounding-Box Mining","created":"2021-11-30","cited_by_count":15,"area":null},{"id":"2209.08263","title":"Scalable SoftGroup for 3D Instance Segmentation on Point Clouds","created":"2022-09-17","cited_by_count":15,"area":null},{"id":"2302.14746","title":"Mask3D: Pre-training 2D Vision Transformers by Learning Masked 3D Priors","created":"2023-02-28","cited_by_count":15,"area":null},{"id":"2210.05593","title":"Prototypical VoteNet for Few-Shot 3D Point Cloud Object Detection","created":"2022-10-11","cited_by_count":14,"area":null},{"id":"2211.09375","title":"3D-QueryIS: A Query-based Framework for 3D Instance Segmentation","created":"2022-11-17","cited_by_count":14,"area":null},{"id":"2401.06704","title":"Scalable 3D Panoptic Segmentation As Superpoint Graph Clustering","created":"2024-01-12","cited_by_count":14,"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":"2506.16991","title":"ForestFormer3D: A Unified Framework for End-to-End Segmentation of Forest LiDAR 3D Point Clouds","created":"2025-06-20","cited_by_count":13,"area":null},{"id":"2202.09715","title":"ARM3D: Attention-based relation module for indoor 3D object detection","created":"2022-02-20","cited_by_count":11,"area":null},{"id":"2203.07186","title":"LiDAR-based 4D Panoptic Segmentation via Dynamic Shifting Network","created":"2022-03-14","cited_by_count":11,"area":null},{"id":"2312.13641","title":"SPGroup3D: Superpoint Grouping Network for Indoor 3D Object Detection","created":"2023-12-21","cited_by_count":11,"area":null},{"id":"2412.01539","title":"The Bare Necessities: Designing Simple, Effective Open-Vocabulary Scene Graphs","created":"2024-12-02","cited_by_count":11,"area":null},{"id":"2506.17891","title":"Relation3D: Enhancing Relation Modeling for Point Cloud Instance Segmentation","created":"2025-06-22","cited_by_count":11,"area":null},{"id":"2309.14737","title":"Volumetric Semantically Consistent 3D Panoptic Mapping","created":"2023-09-26","cited_by_count":10,"area":null},{"id":"2107.03180","title":"HIDA: Towards Holistic Indoor Understanding for the Visually Impaired via Semantic Instance Segmentation with a Wearable Solid-State LiDAR Sensor","created":"2021-07-07","cited_by_count":9,"area":null},{"id":"2309.00828","title":"When 3D Bounding-Box Meets SAM: Point Cloud Instance Segmentation with Weak-and-Noisy Supervision","created":"2023-09-02","cited_by_count":9,"area":null},{"id":"2403.06403","title":"PointSeg: A Training-Free Paradigm for 3D Scene Segmentation via Foundation Models","created":"2024-03-11","cited_by_count":9,"area":null},{"id":"2403.15019","title":"BSNet: Box-Supervised Simulation-assisted Mean Teacher for 3D Instance Segmentation","created":"2024-03-22","cited_by_count":9,"area":null},{"id":"2210.02834","title":"Robust Double-Encoder Network for RGB-D Panoptic Segmentation","created":"2022-10-06","cited_by_count":8,"area":null},{"id":"2304.13980","title":"A Review of Panoptic Segmentation for Mobile Mapping Point Clouds","created":"2023-04-27","cited_by_count":8,"area":null},{"id":"2307.02877","title":"Towards accurate instance segmentation in large-scale LiDAR point clouds","created":"2023-07-06","cited_by_count":8,"area":null},{"id":"2309.14338","title":"3D Indoor Instance Segmentation in an Open-World","created":"2023-09-25","cited_by_count":7,"area":null},{"id":"2310.12464","title":"Lidar Panoptic Segmentation and Tracking without Bells and Whistles","created":"2023-10-19","cited_by_count":7,"area":null},{"id":"2203.09375","title":"Neural Part Priors: Learning to Optimize Part-Based Object Completion in RGB-D Scans","created":"2022-03-17","cited_by_count":6,"area":null},{"id":"2305.06973","title":"FreePoint: Unsupervised Point Cloud Instance Segmentation","created":"2023-05-11","cited_by_count":6,"area":null},{"id":"2405.02911","title":"Multimodal Sense-Informed Prediction of 3D Human Motions","created":"2024-05-05","cited_by_count":6,"area":null},{"id":"2511.11702","title":"Task-Aware 3D Affordance Segmentation via 2D Guidance and Geometric Refinement","created":"2025-11-12","cited_by_count":6,"area":null},{"id":"2103.09160","title":"LRGNet: Learnable Region Growing for Class-Agnostic Point Cloud Segmentation","created":"2021-03-16","cited_by_count":5,"area":null},{"id":"2210.08159","title":"Dynamics-aware Adversarial Attack of Adaptive Neural Networks","created":"2022-10-15","cited_by_count":5,"area":null},{"id":"2503.14493","title":"State Space Model Meets Transformer: A New Paradigm for 3D Object Detection","created":"2025-03-18","cited_by_count":5,"area":null},{"id":"2208.05110","title":"Collaborative Propagation on Multiple Instance Graphs for 3D Instance Segmentation with Single-point Supervision","created":"2022-08-10","cited_by_count":4,"area":null},{"id":"2411.01781","title":"MSTA3D: Multi-scale Twin-attention for 3D Instance Segmentation","created":"2024-11-04","cited_by_count":4,"area":null},{"id":"2411.14179","title":"CompetitorFormer: Competitor Transformer for 3D Instance Segmentation","created":"2024-11-21","cited_by_count":4,"area":null},{"id":"2507.05211","title":"All in One: Visual-Description-Guided Unified Point Cloud Segmentation","created":"2025-07-07","cited_by_count":4,"area":null},{"id":"2509.16098","title":"SegDINO3D: 3D Instance Segmentation Empowered by Both Image-Level and Object-Level 2D Features","created":"2025-09-19","cited_by_count":4,"area":null},{"id":"2509.23541","title":"OVSeg3R: Learn Open-vocabulary Instance Segmentation from 2D via 3D Reconstruction","created":"2025-09-28","cited_by_count":4,"area":null},{"id":"2107.08392","title":"Dynamic Convolution for 3D Point Cloud Instance Segmentation","created":"2021-07-18","cited_by_count":3,"area":null},{"id":"2203.01152","title":"DisARM: Displacement Aware Relation Module for 3D Detection","created":"2022-03-02","cited_by_count":3,"area":null},{"id":"2206.02366","title":"Scan2Part: Fine-grained and Hierarchical Part-level Understanding of Real-World 3D Scans","created":"2022-06-06","cited_by_count":3,"area":null},{"id":"2207.10859","title":"Geodesic-Former: a Geodesic-Guided Few-shot 3D Point Cloud Instance Segmenter","created":"2022-07-22","cited_by_count":3,"area":null},{"id":"2308.01721","title":"Weakly Supervised 3D Instance Segmentation without Instance-level Annotations","created":"2023-08-03","cited_by_count":3,"area":null},{"id":"2310.06385","title":"3DS-SLAM: A 3D Object Detection based Semantic SLAM towards Dynamic Indoor Environments","created":"2023-10-10","cited_by_count":3,"area":null}],"next_cursor":"100"}