{"list":"other","total":58,"rows":[{"id":"1505.04597","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","created":"2015-05-18","cited_by_count":19713},{"id":"2011.13456","title":"Score-Based Generative Modeling through Stochastic Differential Equations","created":"2020-11-26","cited_by_count":9122},{"id":"1611.07004","title":"Image-to-Image Translation with Conditional Adversarial Networks","created":"2016-11-21","cited_by_count":4527},{"id":"1903.11027","title":"nuScenes: A multimodal dataset for autonomous driving","created":"2019-03-26","cited_by_count":4523},{"id":"1907.05600","title":"Generative Modeling by Estimating Gradients of the Data Distribution","created":"2019-07-12","cited_by_count":4101},{"id":"1312.6114","title":"Auto-Encoding Variational Bayes","created":"2013-12-20","cited_by_count":4053},{"id":"1512.03012","title":"ShapeNet: An Information-Rich 3D Model Repository","created":"2015-12-09","cited_by_count":2897},{"id":"1711.03938","title":"CARLA: An Open Urban Driving Simulator","created":"2017-11-10","cited_by_count":2449},{"id":"1801.07829","title":"Dynamic Graph CNN for Learning on Point Clouds","created":"2018-01-24","cited_by_count":2223},{"id":"1812.05784","title":"PointPillars: Fast Encoders for Object Detection from Point Clouds","created":"2018-12-14","cited_by_count":1715},{"id":"1904.08889","title":"KPConv: Flexible and Deformable Convolution for Point Clouds","created":"2019-04-18","cited_by_count":1205},{"id":"2006.09011","title":"Improved Techniques for Training Score-Based Generative Models","created":"2020-06-16","cited_by_count":1043},{"id":"1612.00603","title":"A Point Set Generation Network for 3D Object Reconstruction from a Single Image","created":"2016-12-02","cited_by_count":979},{"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":"2103.01458","title":"Diffusion Probabilistic Models for 3D Point Cloud Generation","created":"2021-03-02","cited_by_count":735},{"id":"1611.07759","title":"Multi-View 3D Object Detection Network for Autonomous Driving","created":"2016-11-23","cited_by_count":724},{"id":"1811.07246","title":"PointConv: Deep Convolutional Networks on 3D Point Clouds","created":"2018-11-17","cited_by_count":657},{"id":"1604.00449","title":"3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction","created":"2016-04-02","cited_by_count":588},{"id":"1911.11236","title":"RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds","created":"2019-11-25","cited_by_count":585},{"id":"2109.13410","title":"KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D","created":"2021-09-28","cited_by_count":575},{"id":"1505.00880","title":"Multi-view Convolutional Neural Networks for 3D Shape Recognition","created":"2015-05-05","cited_by_count":565},{"id":"1906.12320","title":"PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows","created":"2019-06-28","cited_by_count":488},{"id":"1801.10130","title":"Spherical CNNs","created":"2018-01-30","cited_by_count":456},{"id":"1905.07088","title":"Sliced Score Matching: A Scalable Approach to Density and Score Estimation","created":"2019-05-17","cited_by_count":384},{"id":"1902.06326","title":"PIXOR: Real-time 3D Object Detection from Point Clouds","created":"2019-02-17","cited_by_count":358},{"id":"1907.03739","title":"Point-Voxel CNN for Efficient 3D Deep Learning","created":"2019-07-08","cited_by_count":343},{"id":"1703.03130","title":"A Structured Self-attentive Sentence Embedding","created":"2017-03-09","cited_by_count":318},{"id":"1704.02901","title":"Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs","created":"2017-04-10","cited_by_count":310},{"id":"1807.03247","title":"An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution","created":"2018-07-09","cited_by_count":307},{"id":"1803.11527","title":"SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters","created":"2018-03-30","cited_by_count":261},{"id":"2008.06520","title":"Learning Gradient Fields for Shape Generation","created":"2020-08-14","cited_by_count":245},{"id":"1604.03265","title":"Volumetric and Multi-View CNNs for Object Classification on 3D Data","created":"2016-04-12","cited_by_count":240},{"id":"1710.07368","title":"SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud","created":"2017-10-19","cited_by_count":232},{"id":"1801.06761","title":"PU-Net: Point Cloud Upsampling Network","created":"2018-01-21","cited_by_count":209},{"id":"2111.01007","title":"Projected GANs Converge Faster","created":"2021-11-01","cited_by_count":208},{"id":"1905.06292","title":"3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions","created":"2019-05-15","cited_by_count":173},{"id":"2101.06742","title":"Deep Parametric Continuous Convolutional Neural Networks","created":"2021-01-17","cited_by_count":161},{"id":"1802.08275","title":"SPLATNet: Sparse Lattice Networks for Point Cloud Processing","created":"2018-02-22","cited_by_count":158},{"id":"1809.00916","title":"OCNet: Object Context Network for Scene Parsing","created":"2018-09-04","cited_by_count":140},{"id":"2006.09348","title":"LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World","created":"2020-06-16","cited_by_count":137},{"id":"1608.07916","title":"Vehicle Detection from 3D Lidar Using Fully Convolutional Network","created":"2016-08-29","cited_by_count":107},{"id":"1810.05591","title":"PointGrow: Autoregressively Learned Point Cloud Generation with Self-Attention","created":"2018-10-12","cited_by_count":105},{"id":"1807.03520","title":"Multiresolution Tree Networks for 3D Point Cloud Processing","created":"2018-07-10","cited_by_count":91},{"id":"1908.04512","title":"Interpolated Convolutional Networks for 3D Point Cloud Understanding","created":"2019-08-13","cited_by_count":86},{"id":"1803.05827","title":"Local Spectral Graph Convolution for Point Set Feature Learning","created":"2018-03-15","cited_by_count":84},{"id":"2111.12083","title":"VISTA 2.0: An Open, Data-driven Simulator for Multimodal Sensing and Policy Learning for Autonomous Vehicles","created":"2021-11-23","cited_by_count":81},{"id":"1810.05795","title":"Point Cloud GAN","created":"2018-10-13","cited_by_count":79},{"id":"1812.01180","title":"Deep Generative Modeling of LiDAR Data","created":"2018-12-04","cited_by_count":71},{"id":"1907.12704","title":"Multi-Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point Clouds from Multiple Angles by Joint Self-Reconstruction and Half-to-Half Prediction","created":"2019-07-30","cited_by_count":66},{"id":"1811.07112","title":"Augmented LiDAR Simulator for Autonomous Driving","created":"2018-11-17","cited_by_count":41},{"id":"2103.15326","title":"Fooling LiDAR Perception via Adversarial Trajectory Perturbation","created":"2021-03-29","cited_by_count":25},{"id":"1905.07290","title":"LiDAR Sensor modeling and Data augmentation with GANs for Autonomous driving","created":"2019-05-17","cited_by_count":22},{"id":"2111.12137","title":"Learning Interactive Driving Policies via Data-driven Simulation","created":"2021-11-23","cited_by_count":17},{"id":"2204.11797","title":"PVNAS: 3D Neural Architecture Search with Point-Voxel Convolution","created":"2022-04-25","cited_by_count":16},{"id":"2112.00050","title":"Pattern-Aware Data Augmentation for LiDAR 3D Object Detection","created":"2021-11-30","cited_by_count":15},{"id":"2003.07521","title":"Energy-Based Processes for Exchangeable Data","created":"2020-03-17","cited_by_count":10},{"id":"1811.07605","title":"Adversarial Autoencoders for Compact Representations of 3D Point Clouds","created":"2018-11-19","cited_by_count":4}],"next_cursor":null}