{"list":"other","total":78,"rows":[{"id":"1910.10683","title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","created":"2019-10-23","cited_by_count":14599},{"id":"2103.14030","title":"Swin Transformer: Hierarchical Vision Transformer using Shifted Windows","created":"2021-03-25","cited_by_count":12139},{"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":"2011.00931","title":"Point Transformer","created":"2020-11-02","cited_by_count":1470},{"id":"2107.06278","title":"Per-Pixel Classification is Not All You Need for Semantic Segmentation","created":"2021-07-13","cited_by_count":1152},{"id":"2106.13230","title":"Video Swin Transformer","created":"2021-06-24","cited_by_count":1091},{"id":"1709.02371","title":"PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume","created":"2017-09-07","cited_by_count":968},{"id":"1704.07813","title":"Unsupervised Learning of Depth and Ego-Motion from Video","created":"2017-04-25","cited_by_count":782},{"id":"1911.02620","title":"Argoverse: 3D Tracking and Forecasting with Rich Maps","created":"2019-11-06","cited_by_count":732},{"id":"1603.08182","title":"3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions","created":"2016-03-27","cited_by_count":336},{"id":"1905.03304","title":"Deep Closest Point: Learning Representations for Point Cloud Registration","created":"2019-05-08","cited_by_count":321},{"id":"2011.13005","title":"PREDATOR: Registration of 3D Point Clouds with Low Overlap","created":"2020-11-25","cited_by_count":290},{"id":"2001.07715","title":"TEASER: Fast and Certifiable Point Cloud Registration","created":"2020-01-21","cited_by_count":274},{"id":"1903.05711","title":"PointNetLK: Robust & Efficient Point Cloud Registration using PointNet","created":"2019-03-13","cited_by_count":233},{"id":"2004.11540","title":"Deep Global Registration","created":"2020-04-24","cited_by_count":229},{"id":"2202.06688","title":"Geometric Transformer for Fast and Robust Point Cloud Registration","created":"2022-02-14","cited_by_count":202},{"id":"2003.13479","title":"RPM-Net: Robust Point Matching using Learned Features","created":"2020-03-30","cited_by_count":182},{"id":"1802.02669","title":"PPFNet: Global Context Aware Local Features for Robust 3D Point Matching","created":"2018-02-07","cited_by_count":181},{"id":"2003.03164","title":"D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features","created":"2020-03-06","cited_by_count":177},{"id":"1811.06879","title":"The Perfect Match: 3D Point Cloud Matching with Smoothed Densities","created":"2018-11-16","cited_by_count":169},{"id":"2505.17685","title":"FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving","created":"2025-05-23","cited_by_count":166},{"id":"2110.14076","title":"CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration","created":"2021-10-26","cited_by_count":152},{"id":"2011.12149","title":"SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration","created":"2020-11-24","cited_by_count":142},{"id":"2103.05465","title":"PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency","created":"2021-03-09","cited_by_count":142},{"id":"1808.10322","title":"PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors","created":"2018-08-30","cited_by_count":141},{"id":"2303.05367","title":"Rethinking Range View Representation for LiDAR Segmentation","created":"2023-03-09","cited_by_count":128},{"id":"2005.01014","title":"Feature-metric Registration: A Fast Semi-supervised Approach for Robust Point Cloud Registration without Correspondences","created":"2020-05-03","cited_by_count":109},{"id":"1807.09413","title":"3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration","created":"2018-07-25","cited_by_count":103},{"id":"2103.04256","title":"Robust Point Cloud Registration Framework Based on Deep Graph Matching","created":"2021-03-07","cited_by_count":97},{"id":"2203.14517","title":"REGTR: End-to-end Point Cloud Correspondences with Transformers","created":"2022-03-28","cited_by_count":96},{"id":"2209.03954","title":"Learning to Generate Realistic LiDAR Point Clouds","created":"2022-09-08","cited_by_count":93},{"id":"2008.09088","title":"DeepGMR: Learning Latent Gaussian Mixture Models for Registration","created":"2020-08-20","cited_by_count":91},{"id":"2509.22548","title":"JanusVLN: Decoupling Semantics and Spatiality with Dual Implicit Memory for Vision-Language Navigation","created":"2025-09-26","cited_by_count":89},{"id":"2111.12591","title":"Lepard: Learning partial point cloud matching in rigid and deformable scenes","created":"2021-11-24","cited_by_count":85},{"id":"2305.10854","title":"3D Registration with Maximal Cliques","created":"2023-05-18","cited_by_count":84},{"id":"2308.03768","title":"GeoTransformer: Fast and Robust Point Cloud Registration with Geometric Transformer","created":"2023-07-25","cited_by_count":84},{"id":"1905.04153","title":"DeepICP: An End-to-End Deep Neural Network for 3D Point Cloud Registration","created":"2019-05-10","cited_by_count":77},{"id":"2301.10222","title":"RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Driving","created":"2023-01-24","cited_by_count":76},{"id":"2403.06467","title":"Point Mamba: A Novel Point Cloud Backbone Based on State Space Model with Octree-Based Ordering Strategy","created":"2024-03-11","cited_by_count":73},{"id":"2303.08231","title":"Rotation-Invariant Transformer for Point Cloud Matching","created":"2023-03-14","cited_by_count":69},{"id":"2311.11016","title":"SNI-SLAM: Semantic Neural Implicit SLAM","created":"2023-11-18","cited_by_count":65},{"id":"2203.14453","title":"SC^2-PCR: A Second Order Spatial Compatibility for Efficient and Robust Point Cloud Registration","created":"2022-03-28","cited_by_count":62},{"id":"1904.08242","title":"LO-Net: Deep Real-time Lidar Odometry","created":"2019-04-17","cited_by_count":60},{"id":"2107.11992","title":"HRegNet: A Hierarchical Network for Large-scale Outdoor LiDAR Point Cloud Registration","created":"2021-07-26","cited_by_count":48},{"id":"2003.05855","title":"End-to-End Learning Local Multi-view Descriptors for 3D Point Clouds","created":"2020-03-12","cited_by_count":47},{"id":"1709.05056","title":"Learning Compact Geometric Features","created":"2017-09-15","cited_by_count":45},{"id":"2407.01702","title":"SeFlow: A Self-Supervised Scene Flow Method in Autonomous Driving","created":"2024-07-01","cited_by_count":39},{"id":"2303.12384","title":"RegFormer: An Efficient Projection-Aware Transformer Network for Large-Scale Point Cloud Registration","created":"2023-03-22","cited_by_count":37},{"id":"2010.05762","title":"Hierarchical Attention Learning of Scene Flow in 3D Point Clouds","created":"2020-10-12","cited_by_count":35},{"id":"2012.00972","title":"PWCLO-Net: Deep LiDAR Odometry in 3D Point Clouds Using Hierarchical Embedding Mask Optimization","created":"2020-12-02","cited_by_count":35},{"id":"2207.09143","title":"What Matters for 3D Scene Flow Network","created":"2022-07-19","cited_by_count":31},{"id":"2401.16122","title":"DeFlow: Decoder of Scene Flow Network in Autonomous Driving","created":"2024-01-29","cited_by_count":30},{"id":"2403.18274","title":"DVLO: Deep Visual-LiDAR Odometry with Local-to-Global Feature Fusion and Bi-Directional Structure Alignment","created":"2024-03-27","cited_by_count":26},{"id":"2111.02135","title":"Efficient 3D Deep LiDAR Odometry","created":"2021-11-03","cited_by_count":25},{"id":"2209.13252","title":"RIGA: Rotation-Invariant and Globally-Aware Descriptors for Point Cloud Registration","created":"2022-09-27","cited_by_count":25},{"id":"2403.11247","title":"Compact 3D Gaussian Splatting For Dense Visual SLAM","created":"2024-03-17","cited_by_count":25},{"id":"2004.03796","title":"DMLO: Deep Matching LiDAR Odometry","created":"2020-04-08","cited_by_count":20},{"id":"2402.18146","title":"3DSFLabelling: Boosting 3D Scene Flow Estimation by Pseudo Auto-labelling","created":"2024-02-28","cited_by_count":16},{"id":"2308.04383","title":"DELFlow: Dense Efficient Learning of Scene Flow for Large-Scale Point Clouds","created":"2023-08-08","cited_by_count":14},{"id":"2412.20211","title":"Generative Regression Based Watch Time Prediction for Short-Video Recommendation","created":"2024-12-28","cited_by_count":13},{"id":"2507.01439","title":"TurboReg: TurboClique for Robust and Efficient Point Cloud Registration","created":"2025-07-02","cited_by_count":13},{"id":"2307.09788","title":"Density-invariant Features for Distant Point Cloud Registration","created":"2023-07-19","cited_by_count":12},{"id":"2506.14511","title":"MOL: Joint Estimation of Micro-Expression, Optical Flow, and Landmark via Transformer-Graph-Style Convolution","created":"2025-06-17","cited_by_count":12},{"id":"2304.07773","title":"PCPNet: An Efficient and Semantic-Enhanced Transformer Network for Point Cloud Prediction","created":"2023-04-16","cited_by_count":11},{"id":"2010.09343","title":"SelfVoxeLO: Self-supervised LiDAR Odometry with Voxel-based Deep Neural Networks","created":"2020-10-19","cited_by_count":10},{"id":"2507.12062","title":"MS-DETR: Towards Effective Video Moment Retrieval and Highlight Detection by Joint Motion-Semantic Learning","created":"2025-07-16","cited_by_count":10},{"id":"2308.07153","title":"DELO: Deep Evidential LiDAR Odometry using Partial Optimal Transport","created":"2023-08-14","cited_by_count":8},{"id":"2507.10358","title":"Fine-Grained Zero-Shot Object Detection","created":"2025-07-14","cited_by_count":8},{"id":"2507.22454","title":"TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation","created":"2025-07-30","cited_by_count":7},{"id":"2202.13353","title":"Robust Self-Supervised LiDAR Odometry via Representative Structure Discovery and 3D Inherent Error Modeling","created":"2022-02-27","cited_by_count":6},{"id":"2406.17530","title":"Point Tree Transformer for Point Cloud Registration","created":"2024-06-25","cited_by_count":5},{"id":"2502.02163","title":"Progressive Correspondence Regenerator for Robust 3D Registration","created":"2025-02-04","cited_by_count":5},{"id":"2507.19950","title":"RARE: Refine Any Registration of Pairwise Point Clouds via Zero-Shot Learning","created":"2025-07-26","cited_by_count":5},{"id":"2511.07241","title":"4DSTR: Advancing Generative 4D Gaussians with Spatial-Temporal Rectification for High-Quality and Consistent 4D Generation","created":"2025-11-10","cited_by_count":5},{"id":"2405.14241","title":"NeuroGauss4D-PCI: 4D Neural Fields and Gaussian Deformation Fields for Point Cloud Interpolation","created":"2024-05-23","cited_by_count":3},{"id":"2509.06023","title":"DVLO4D: Deep Visual-Lidar Odometry with Sparse Spatial-temporal Fusion","created":"2025-09-07","cited_by_count":3}],"next_cursor":null}