{"list":"other","total":57,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1612.00593","title":"PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation","created":"2016-12-02","cited_by_count":5248},{"id":"1608.03983","title":"SGDR: Stochastic Gradient Descent with Warm Restarts","created":"2016-08-13","cited_by_count":5045},{"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":"1702.04405","title":"ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes","created":"2017-02-14","cited_by_count":3117},{"id":"1801.07829","title":"Dynamic Graph CNN for Learning on Point Clouds","created":"2018-01-24","cited_by_count":2223},{"id":"2011.00931","title":"Point Transformer","created":"2020-11-02","cited_by_count":1470},{"id":"1904.08889","title":"KPConv: Flexible and Deformable Convolution for Point Clouds","created":"2019-04-18","cited_by_count":1205},{"id":"1801.07791","title":"PointCNN: Convolution On $\\mathcal{X}$-Transformed Points","created":"2018-01-23","cited_by_count":764},{"id":"1711.10275","title":"3D Semantic Segmentation with Submanifold Sparse Convolutional Networks","created":"2017-11-28","cited_by_count":748},{"id":"2001.05566","title":"Image Segmentation Using Deep Learning: A Survey","created":"2020-01-15","cited_by_count":660},{"id":"1811.07246","title":"PointConv: Deep Convolutional Networks on 3D Point Clouds","created":"2018-11-17","cited_by_count":657},{"id":"1911.11236","title":"RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds","created":"2019-11-25","cited_by_count":585},{"id":"1912.12033","title":"Deep Learning for 3D Point Clouds: A Survey","created":"2019-12-27","cited_by_count":558},{"id":"1908.04616","title":"Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data","created":"2019-08-13","cited_by_count":532},{"id":"1904.01169","title":"Res2Net: A New Multi-scale Backbone Architecture","created":"2019-04-02","cited_by_count":470},{"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":"1711.09869","title":"Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs","created":"2017-11-27","cited_by_count":385},{"id":"1907.03670","title":"From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network","created":"2019-07-08","cited_by_count":368},{"id":"1904.07601","title":"Relation-Shape Convolutional Neural Network for Point Cloud Analysis","created":"2019-04-16","cited_by_count":346},{"id":"1803.11527","title":"SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters","created":"2018-03-30","cited_by_count":261},{"id":"2003.00492","title":"PointASNL: Robust Point Clouds Processing using Nonlocal Neural Networks with Adaptive Sampling","created":"2020-03-01","cited_by_count":239},{"id":"2103.14635","title":"PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds","created":"2021-03-26","cited_by_count":211},{"id":"2203.14508","title":"Stratified Transformer for 3D Point Cloud Segmentation","created":"2022-03-28","cited_by_count":167},{"id":"1904.09146","title":"Salient Object Detection in the Deep Learning Era: An In-Depth Survey","created":"2019-04-19","cited_by_count":164},{"id":"2101.06742","title":"Deep Parametric Continuous Convolutional Neural Networks","created":"2021-01-17","cited_by_count":161},{"id":"1803.10091","title":"Point Convolutional Neural Networks by Extension Operators","created":"2018-03-27","cited_by_count":154},{"id":"1904.03375","title":"Modeling Point Clouds with Self-Attention and Gumbel Subset Sampling","created":"2019-04-06","cited_by_count":151},{"id":"1712.05245","title":"Pointwise Convolutional Neural Networks","created":"2017-12-14","cited_by_count":127},{"id":"1908.06295","title":"ShellNet: Efficient Point Cloud Convolutional Neural Networks using Concentric Shells Statistics","created":"2019-08-17","cited_by_count":104},{"id":"1909.03669","title":"DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing","created":"2019-09-09","cited_by_count":104},{"id":"2112.04702","title":"Fast Point Transformer","created":"2021-12-09","cited_by_count":104},{"id":"1912.02984","title":"Grid-GCN for Fast and Scalable Point Cloud Learning","created":"2019-12-06","cited_by_count":103},{"id":"1811.02565","title":"Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-based Sequence to Sequence Network","created":"2018-11-06","cited_by_count":100},{"id":"2007.13138","title":"Virtual Multi-view Fusion for 3D Semantic Segmentation","created":"2020-07-26","cited_by_count":99},{"id":"2103.14326","title":"Bidirectional Projection Network for Cross Dimension Scene Understanding","created":"2021-03-26","cited_by_count":95},{"id":"2007.01294","title":"A Closer Look at Local Aggregation Operators in Point Cloud Analysis","created":"2020-07-02","cited_by_count":87},{"id":"1912.03663","title":"SampleNet: Differentiable Point Cloud Sampling","created":"2019-12-08","cited_by_count":74},{"id":"1909.10469","title":"Hierarchical Point-Edge Interaction Network for Point Cloud Semantic Segmentation","created":"2019-09-23","cited_by_count":68},{"id":"1904.08017","title":"A-CNN: Annularly Convolutional Neural Networks on Point Clouds","created":"2019-04-16","cited_by_count":66},{"id":"2007.06888","title":"JSENet: Joint Semantic Segmentation and Edge Detection Network for 3D Point Clouds","created":"2020-07-14","cited_by_count":62},{"id":"1904.08242","title":"LO-Net: Deep Real-time Lidar Odometry","created":"2019-04-17","cited_by_count":60},{"id":"2108.08035","title":"Adaptive Graph Convolution for Point Cloud Analysis","created":"2021-08-18","cited_by_count":60},{"id":"1909.09287","title":"Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds","created":"2019-09-20","cited_by_count":57},{"id":"2202.09507","title":"PMP-Net++: Point Cloud Completion by Transformer-Enhanced Multi-step Point Moving Paths","created":"2022-02-19","cited_by_count":57},{"id":"2203.05272","title":"Contrastive Boundary Learning for Point Cloud Segmentation","created":"2022-03-10","cited_by_count":56},{"id":"2002.10701","title":"FPConv: Learning Local Flattening for Point Convolution","created":"2020-02-25","cited_by_count":55},{"id":"2107.02389","title":"Learning Semantic Segmentation of Large-Scale Point Clouds with Random Sampling","created":"2021-07-06","cited_by_count":51},{"id":"1904.08506","title":"Adaptive Hierarchical Down-Sampling for Point Cloud Classification","created":"2019-04-11","cited_by_count":40},{"id":"2108.12468","title":"Learning Inner-Group Relations on Point Clouds","created":"2021-08-27","cited_by_count":29},{"id":"1912.10775","title":"Point2Node: Correlation Learning of Dynamic-Node for Point Cloud Feature Modeling","created":"2019-12-23","cited_by_count":25},{"id":"1911.05277","title":"Exploiting Local and Global Structure for Point Cloud Semantic Segmentation with Contextual Point Representations","created":"2019-11-13","cited_by_count":10},{"id":"2108.07378","title":"PnP-3D: A Plug-and-Play for 3D Point Clouds","created":"2021-08-16","cited_by_count":10},{"id":"1906.10887","title":"Spatial Transformer for 3D Point Clouds","created":"2019-06-26","cited_by_count":6},{"id":"2108.12856","title":"Differentiable Convolution Search for Point Cloud Processing","created":"2021-08-29","cited_by_count":3}],"next_cursor":null}