{"total":105,"rows":[{"id":"2110.04202","title":"Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation","created":"2021-10-08","cited_by_count":177,"area":null},{"id":"2103.05346","title":"ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection","created":"2021-03-09","cited_by_count":159,"area":null},{"id":"2112.00463","title":"The Norm Must Go On: Dynamic Unsupervised Domain Adaptation by Normalization","created":"2021-12-01","cited_by_count":131,"area":null},{"id":"2108.06709","title":"SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation","created":"2021-08-15","cited_by_count":94,"area":null},{"id":"2301.00265","title":"Source-Free Unsupervised Domain Adaptation: A Survey","created":"2022-12-31","cited_by_count":80,"area":null},{"id":"2107.05399","title":"Transfer Learning from Synthetic to Real LiDAR Point Cloud for Semantic Segmentation","created":"2021-07-12","cited_by_count":76,"area":null},{"id":"2207.05444","title":"Category-Level 6D Object Pose and Size Estimation using Self-Supervised Deep Prior Deformation Networks","created":"2022-07-12","cited_by_count":74,"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":"2302.14040","title":"Permutation Equivariant Neural Functionals","created":"2023-02-27","cited_by_count":70,"area":null},{"id":"2103.14357","title":"VDM-DA: Virtual Domain Modeling for Source Data-free Domain Adaptation","created":"2021-03-26","cited_by_count":69,"area":null},{"id":"2107.11355","title":"Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency","created":"2021-07-23","cited_by_count":63,"area":null},{"id":"2108.06682","title":"ST3D++: Denoised Self-training for Unsupervised Domain Adaptation on 3D Object Detection","created":"2021-08-15","cited_by_count":57,"area":null},{"id":"2203.14956","title":"LiDAR Distillation: Bridging the Beam-Induced Domain Gap for 3D Object Detection","created":"2022-03-28","cited_by_count":55,"area":null},{"id":"2106.02377","title":"A Survey on Deep Domain Adaptation for LiDAR Perception","created":"2021-06-04","cited_by_count":47,"area":null},{"id":"2101.07253","title":"Cross-modal Learning for Domain Adaptation in 3D Semantic Segmentation","created":"2021-01-18","cited_by_count":40,"area":null},{"id":"2204.02811","title":"BMD: A General Class-balanced Multicentric Dynamic Prototype Strategy for Source-free Domain Adaptation","created":"2022-04-06","cited_by_count":39,"area":null},{"id":"2307.01217","title":"FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy","created":"2023-07-01","cited_by_count":36,"area":null},{"id":"2205.14566","title":"ProxyMix: Proxy-based Mixup Training with Label Refinery for Source-Free Domain Adaptation","created":"2022-05-29","cited_by_count":34,"area":null},{"id":"2108.09169","title":"Geometry-Aware Self-Training for Unsupervised Domain Adaptationon Object Point Clouds","created":"2021-08-20","cited_by_count":31,"area":null},{"id":"2203.16895","title":"Deformation and Correspondence Aware Unsupervised Synthetic-to-Real Scene Flow Estimation for Point Clouds","created":"2022-03-31","cited_by_count":28,"area":null},{"id":"2212.00244","title":"CL3D: Unsupervised Domain Adaptation for Cross-LiDAR 3D Detection","created":"2022-12-01","cited_by_count":27,"area":null},{"id":"2112.09343","title":"Domain Adaptation on Point Clouds via Geometry-Aware Implicits","created":"2021-12-17","cited_by_count":26,"area":null},{"id":"2208.08052","title":"Imperceptible and Robust Backdoor Attack in 3D Point Cloud","created":"2022-08-17","cited_by_count":25,"area":null},{"id":"2211.11432","title":"MATE: Masked Autoencoders are Online 3D Test-Time Learners","created":"2022-11-21","cited_by_count":23,"area":null},{"id":"2308.16481","title":"Point-TTA: Test-Time Adaptation for Point Cloud Registration Using Multitask Meta-Auxiliary Learning","created":"2023-08-31","cited_by_count":23,"area":null},{"id":"2204.07311","title":"MetaSets: Meta-Learning on Point Sets for Generalizable Representations","created":"2022-04-15","cited_by_count":22,"area":null},{"id":"2303.05886","title":"Bi3D: Bi-domain Active Learning for Cross-domain 3D Object Detection","created":"2023-03-10","cited_by_count":22,"area":null},{"id":"2103.14198","title":"Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection","created":"2021-03-26","cited_by_count":21,"area":null},{"id":"2107.09783","title":"Unsupervised Domain Adaptation in LiDAR Semantic Segmentation with Self-Supervision and Gated Adapters","created":"2021-07-20","cited_by_count":21,"area":null},{"id":"2304.03251","title":"SALUDA: Surface-based Automotive Lidar Unsupervised Domain Adaptation","created":"2023-04-06","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":"2403.10834","title":"SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation","created":"2024-03-16","cited_by_count":19,"area":null},{"id":"2109.14651","title":"Uncertainty-aware Mean Teacher for Source-free Unsupervised Domain Adaptive 3D Object Detection","created":"2021-09-29","cited_by_count":18,"area":null},{"id":"2310.08117","title":"DUSA: Decoupled Unsupervised Sim2Real Adaptation for Vehicle-to-Everything Collaborative Perception","created":"2023-10-12","cited_by_count":17,"area":null},{"id":"2111.09450","title":"See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain Adaptation","created":"2021-11-17","cited_by_count":15,"area":null},{"id":"2207.03111","title":"Masked Surfel Prediction for Self-Supervised Point Cloud Learning","created":"2022-07-07","cited_by_count":15,"area":null},{"id":"2303.07123","title":"Modality-Agnostic Debiasing for Single Domain Generalization","created":"2023-03-13","cited_by_count":14,"area":null},{"id":"2403.18442","title":"Backpropagation-free Network for 3D Test-time Adaptation","created":"2024-03-27","cited_by_count":14,"area":null},{"id":"2101.02672","title":"SA-Det3D: Self-Attention Based Context-Aware 3D Object Detection","created":"2021-01-07","cited_by_count":13,"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":"2407.08801","title":"DG-PIC: Domain Generalized Point-In-Context Learning for Point Cloud Understanding","created":"2024-07-11","cited_by_count":13,"area":null},{"id":"2302.09886","title":"InOR-Net: Incremental 3D Object Recognition Network for Point Cloud Representation","created":"2023-02-20","cited_by_count":11,"area":null},{"id":"2411.00632","title":"PCoTTA: Continual Test-Time Adaptation for Multi-Task Point Cloud Understanding","created":"2024-11-01","cited_by_count":11,"area":null},{"id":"2104.11021","title":"Cycle and Semantic Consistent Adversarial Domain Adaptation for Reducing Simulation-to-Real Domain Shift in LiDAR Bird's Eye View","created":"2021-04-22","cited_by_count":10,"area":null},{"id":"2110.09355","title":"FAST3D: Flow-Aware Self-Training for 3D Object Detectors","created":"2021-10-18","cited_by_count":10,"area":null},{"id":"2112.06161","title":"Semi-supervised Domain Adaptive Structure Learning","created":"2021-12-12","cited_by_count":10,"area":null},{"id":"2307.04231","title":"Mx2M: Masked Cross-Modality Modeling in Domain Adaptation for 3D Semantic Segmentation","created":"2023-07-09","cited_by_count":10,"area":null},{"id":"2308.16484","title":"Test-Time Adaptation for Point Cloud Upsampling Using Meta-Learning","created":"2023-08-31","cited_by_count":10,"area":null},{"id":"2211.12193","title":"Anatomy-guided domain adaptation for 3D in-bed human pose estimation","created":"2022-11-22","cited_by_count":9,"area":null},{"id":"2304.10179","title":"SCoDA: Domain Adaptive Shape Completion for Real Scans","created":"2023-04-20","cited_by_count":9,"area":null},{"id":"2309.00528","title":"Trust your Good Friends: Source-free Domain Adaptation by Reciprocal Neighborhood Clustering","created":"2023-09-01","cited_by_count":9,"area":null},{"id":"2407.17877","title":"Advancing 3D Point Cloud Understanding through Deep Transfer Learning: A Comprehensive Survey","created":"2024-07-25","cited_by_count":9,"area":null},{"id":"2110.11036","title":"RefRec: Pseudo-labels Refinement via Shape Reconstruction for Unsupervised 3D Domain Adaptation","created":"2021-10-21","cited_by_count":8,"area":null},{"id":"2305.03724","title":"DualCross: Cross-Modality Cross-Domain Adaptation for Monocular BEV Perception","created":"2023-05-05","cited_by_count":8,"area":null},{"id":"2310.01140","title":"Neural Processing of Tri-Plane Hybrid Neural Fields","created":"2023-10-02","cited_by_count":8,"area":null},{"id":"2403.06804","title":"Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction","created":"2024-03-11","cited_by_count":7,"area":null},{"id":"2102.10788","title":"Attention Models for Point Clouds in Deep Learning: A Survey","created":"2021-02-22","cited_by_count":6,"area":null},{"id":"2104.05164","title":"A Learnable Self-supervised Task for Unsupervised Domain Adaptation on Point Clouds","created":"2021-04-12","cited_by_count":6,"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":"2303.15104","title":"Generalizable Local Feature Pre-training for Deformable Shape Analysis","created":"2023-03-27","cited_by_count":6,"area":null},{"id":"2305.09160","title":"SUG: Single-dataset Unified Generalization for 3D Point Cloud Classification","created":"2023-05-16","cited_by_count":6,"area":null},{"id":"2407.12387","title":"HGL: Hierarchical Geometry Learning for Test-time Adaptation in 3D Point Cloud Segmentation","created":"2024-07-17","cited_by_count":6,"area":null},{"id":"2410.20406","title":"Point-PRC: A Prompt Learning Based Regulation Framework for Generalizable Point Cloud Analysis","created":"2024-10-27","cited_by_count":6,"area":null},{"id":"2108.02104","title":"Point Discriminative Learning for Data-efficient 3D Point Cloud Analysis","created":"2021-08-04","cited_by_count":5,"area":null},{"id":"2203.03833","title":"Quasi-Balanced Self-Training on Noise-Aware Synthesis of Object Point Clouds for Closing Domain Gap","created":"2022-03-08","cited_by_count":5,"area":null},{"id":"2206.03726","title":"Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models","created":"2022-06-08","cited_by_count":5,"area":null},{"id":"2308.14126","title":"Synergizing Contrastive Learning and Optimal Transport for 3D Point Cloud Domain Adaptation","created":"2023-08-27","cited_by_count":5,"area":null},{"id":"2309.16936","title":"PC-Adapter: Topology-Aware Adapter for Efficient Domain Adaption on Point Clouds with Rectified Pseudo-label","created":"2023-09-29","cited_by_count":5,"area":null},{"id":"2502.02247","title":"Rotation-Adaptive Point Cloud Domain Generalization via Intricate Orientation Learning","created":"2025-02-04","cited_by_count":5,"area":null},{"id":"2205.12627","title":"Primitive3D: 3D Object Dataset Synthesis from Randomly Assembled Primitives","created":"2022-05-25","cited_by_count":4,"area":null},{"id":"2207.04185","title":"Domain Alignment Meets Fully Test-Time Adaptation","created":"2022-07-09","cited_by_count":4,"area":null},{"id":"2210.09728","title":"3D Scalable Quantum Convolutional Neural Networks for Point Cloud Data Processing in Classification Applications","created":"2022-10-18","cited_by_count":4,"area":null},{"id":"2403.00206","title":"MaskLRF: Self-supervised Pretraining via Masked Autoencoding of Local Reference Frames for Rotation-invariant 3D Point Set Analysis","created":"2024-03-01","cited_by_count":4,"area":null},{"id":"2503.12150","title":"Point-Cache: Test-time Dynamic and Hierarchical Cache for Robust and Generalizable Point Cloud Analysis","created":"2025-03-15","cited_by_count":4,"area":null},{"id":"2503.18384","title":"LiDAR Remote Sensing Meets Weak Supervision: Concepts, Methods, and Perspectives","created":"2025-03-24","cited_by_count":4,"area":null},{"id":"2107.13087","title":"DCL: Differential Contrastive Learning for Geometry-Aware Depth Synthesis","created":"2021-07-27","cited_by_count":3,"area":null},{"id":"2204.10024","title":"Understanding the Domain Gap in LiDAR Object Detection Networks","created":"2022-04-21","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":"2206.13628","title":"Multi-scale Network with Attentional Multi-resolution Fusion for Point Cloud Semantic Segmentation","created":"2022-06-27","cited_by_count":2,"area":null},{"id":"2304.01554","title":"MEnsA: Mix-up Ensemble Average for Unsupervised Multi Target Domain Adaptation on 3D Point Clouds","created":"2023-04-04","cited_by_count":2,"area":null},{"id":"2311.16474","title":"Progressive Classifier and Feature Extractor Adaptation for Unsupervised Domain Adaptation on Point Clouds","created":"2023-11-27","cited_by_count":2,"area":null},{"id":"2401.03765","title":"InvariantOODG: Learning Invariant Features of Point Clouds for Out-of-Distribution Generalization","created":"2024-01-08","cited_by_count":2,"area":null},{"id":"2408.13574","title":"PointDGMamba: Domain Generalization of Point Cloud Classification via Generalized State Space Model","created":"2024-08-24","cited_by_count":2,"area":null},{"id":"2508.17439","title":"Investigating Domain Gaps for Indoor 3D Object Detection","created":"2025-08-24","cited_by_count":2,"area":null},{"id":"2112.05301","title":"Self-Ensemling for 3D Point Cloud Domain Adaption","created":"2021-12-10","cited_by_count":1,"area":null},{"id":"2303.17338","title":"Local region-learning modules for point cloud classification","created":"2023-03-30","cited_by_count":1,"area":null},{"id":"2310.18141","title":"Unsupervised Representation Learning for Diverse Deformable Shape Collections","created":"2023-10-27","cited_by_count":1,"area":null},{"id":"2406.11313","title":"Semi-Supervised Domain Adaptation Using Target-Oriented Domain Augmentation for 3D Object Detection","created":"2024-06-17","cited_by_count":1,"area":null},{"id":"2501.11695","title":"Spatially-Delineated Domain-Adapted AI Classification: An Application for Oncology Data","created":"2025-01-20","cited_by_count":1,"area":null},{"id":"2504.12456","title":"DG-MVP: 3D Domain Generalization via Multiple Views of Point Clouds for Classification","created":"2025-04-16","cited_by_count":1,"area":null},{"id":"2601.23181","title":"Ensuring Semantics in Weights of Implicit Neural Representations through the Implicit Function Theorem","created":"2026-01-30","cited_by_count":1,"area":null},{"id":"2605.15775","title":"Continual Learning of Domain-Invariant Representations","created":"2026-05-15","cited_by_count":1,"area":null},{"id":"2102.07373","title":"Generation For Adaption: A GAN-Based Approach for 3D Domain Adaption with Point Cloud Data","created":"2021-02-15","cited_by_count":0,"area":null},{"id":"2112.11133","title":"Cloud Sphere: A 3D Shape Representation via Progressive Deformation","created":"2021-12-21","cited_by_count":0,"area":null},{"id":"2210.17009","title":"Point-Syn2Real: Semi-Supervised Synthetic-to-Real Cross-Domain Learning for Object Classification in 3D Point Clouds","created":"2022-10-31","cited_by_count":0,"area":null},{"id":"2405.06916","title":"High-order Neighborhoods Know More: HyperGraph Learning Meets Source-free Unsupervised Domain Adaptation","created":"2024-05-11","cited_by_count":0,"area":null},{"id":"2407.18534","title":"Boosting Cross-Domain Point Classification via Distilling Relational Priors from 2D Transformers","created":"2024-07-26","cited_by_count":0,"area":null},{"id":"2409.06956","title":"Bridging Domain Gap of Point Cloud Representations via Self-Supervised Geometric Augmentation","created":"2024-09-11","cited_by_count":0,"area":null},{"id":"2410.02720","title":"Curvature Diversity-Driven Deformation and Domain Alignment for Point Cloud","created":"2024-10-03","cited_by_count":0,"area":null}],"next_cursor":"100"}