{"list":"other","total":67,"rows":[{"id":"2103.00020","title":"Learning Transferable Visual Models From Natural Language Supervision","created":"2021-02-26","cited_by_count":33744},{"id":"1505.04597","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","created":"2015-05-18","cited_by_count":19713},{"id":"2304.02643","title":"Segment Anything","created":"2023-04-05","cited_by_count":8234},{"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":"1606.00915","title":"DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs","created":"2016-06-02","cited_by_count":3241},{"id":"1802.02611","title":"Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation","created":"2018-02-07","cited_by_count":3223},{"id":"2006.09882","title":"Unsupervised Learning of Visual Features by Contrasting Cluster Assignments","created":"2020-06-17","cited_by_count":2857},{"id":"1306.0895","title":"Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances","created":"2013-06-04","cited_by_count":2316},{"id":"1709.06158","title":"Matterport3D: Learning from RGB-D Data in Indoor Environments","created":"2017-09-18","cited_by_count":1376},{"id":"1711.06396","title":"VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection","created":"2017-11-17","cited_by_count":1323},{"id":"1904.08755","title":"4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks","created":"2019-04-18","cited_by_count":1208},{"id":"1904.08889","title":"KPConv: Flexible and Deformable Convolution for Point Clouds","created":"2019-04-18","cited_by_count":1205},{"id":"1711.10275","title":"3D Semantic Segmentation with Submanifold Sparse Convolutional Networks","created":"2017-11-28","cited_by_count":748},{"id":"2111.14819","title":"Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point Modeling","created":"2021-11-29","cited_by_count":653},{"id":"1911.11236","title":"RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds","created":"2019-11-25","cited_by_count":585},{"id":"2211.15654","title":"OpenScene: 3D Scene Understanding with Open Vocabularies","created":"2022-11-28","cited_by_count":559},{"id":"1610.07584","title":"Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling","created":"2016-10-24","cited_by_count":558},{"id":"1911.05371","title":"Self-labelling via simultaneous clustering and representation learning","created":"2019-11-13","cited_by_count":528},{"id":"2007.10985","title":"PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding","created":"2020-07-21","cited_by_count":504},{"id":"1906.12320","title":"PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows","created":"2019-06-28","cited_by_count":488},{"id":"2203.06604","title":"Masked Autoencoders for Point Cloud Self-supervised Learning","created":"2022-03-13","cited_by_count":459},{"id":"1807.06653","title":"Invariant Information Clustering for Unsupervised Image Classification and Segmentation","created":"2018-07-17","cited_by_count":455},{"id":"2011.10033","title":"Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation","created":"2020-11-19","cited_by_count":389},{"id":"1808.00671","title":"PCN: Point Completion Network","created":"2018-08-02","cited_by_count":384},{"id":"2106.13043","title":"AudioCLIP: Extending CLIP to Image, Text and Audio","created":"2021-06-24","cited_by_count":339},{"id":"2302.07241","title":"ConceptFusion: Open-set Multimodal 3D Mapping","created":"2023-02-14","cited_by_count":304},{"id":"2003.14032","title":"PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation","created":"2020-03-31","cited_by_count":275},{"id":"2204.07761","title":"Language-Grounded Indoor 3D Semantic Segmentation in the Wild","created":"2022-04-16","cited_by_count":246},{"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":"1809.08495","title":"SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud","created":"2018-09-22","cited_by_count":228},{"id":"1908.09884","title":"Learning to Discover Novel Visual Categories via Deep Transfer Clustering","created":"2019-08-26","cited_by_count":225},{"id":"1706.01307","title":"Submanifold Sparse Convolutional Networks","created":"2017-06-05","cited_by_count":223},{"id":"2101.02691","title":"Self-Supervised Pretraining of 3D Features on any Point-Cloud","created":"2021-01-07","cited_by_count":217},{"id":"2201.02609","title":"Generalized Category Discovery","created":"2022-01-07","cited_by_count":211},{"id":"2208.12262","title":"MaskCLIP: Masked Self-Distillation Advances Contrastive Language-Image Pretraining","created":"2022-08-25","cited_by_count":187},{"id":"2109.00179","title":"Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds","created":"2021-09-01","cited_by_count":180},{"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":"2109.03805","title":"Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Tracking","created":"2021-09-08","cited_by_count":166},{"id":"1907.10844","title":"PU-GAN: a Point Cloud Upsampling Adversarial Network","created":"2019-07-25","cited_by_count":164},{"id":"2102.04530","title":"(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Network","created":"2021-02-08","cited_by_count":164},{"id":"2108.08536","title":"A Unified Objective for Novel Class Discovery","created":"2021-08-19","cited_by_count":162},{"id":"1808.10322","title":"PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors","created":"2018-08-30","cited_by_count":141},{"id":"2002.09147","title":"SemanticPOSS: A Point Cloud Dataset with Large Quantity of Dynamic Instances","created":"2020-02-21","cited_by_count":123},{"id":"2106.10731","title":"Neighborhood Contrastive Learning for Novel Class Discovery","created":"2021-06-20","cited_by_count":121},{"id":"2005.03871","title":"Point Cloud Completion by Skip-attention Network with Hierarchical Folding","created":"2020-05-08","cited_by_count":106},{"id":"1912.03264","title":"PU-GCN: Point Cloud Upsampling using Graph Convolutional Networks","created":"2019-11-30","cited_by_count":101},{"id":"2004.05551","title":"OpenMix: Reviving Known Knowledge for Discovering Novel Visual Categories in An Open World","created":"2020-04-12","cited_by_count":93},{"id":"2008.00305","title":"Self-supervised Learning of Point Clouds via Orientation Estimation","created":"2020-08-01","cited_by_count":72},{"id":"2002.10893","title":"3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D LIDAR Semantic Segmentation","created":"2020-02-25","cited_by_count":58},{"id":"2104.12673","title":"Joint Representation Learning and Novel Category Discovery on Single- and Multi-modal Data","created":"2021-04-26","cited_by_count":55},{"id":"2202.13589","title":"Unsupervised Point Cloud Representation Learning with Deep Neural Networks: A Survey","created":"2022-02-28","cited_by_count":54},{"id":"2207.09778","title":"CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation","created":"2022-07-20","cited_by_count":54},{"id":"2105.10382","title":"Learning general and distinctive 3D local deep descriptors for point cloud registration","created":"2021-05-21","cited_by_count":42},{"id":"2207.08605","title":"Class-incremental Novel Class Discovery","created":"2022-07-18","cited_by_count":42},{"id":"2207.10659","title":"Novel Class Discovery without Forgetting","created":"2022-07-21","cited_by_count":39},{"id":"2207.09763","title":"GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation","created":"2022-07-20","cited_by_count":35},{"id":"2112.01900","title":"Novel Class Discovery in Semantic Segmentation","created":"2021-12-03","cited_by_count":31},{"id":"2207.01452","title":"Open-world Semantic Segmentation for LIDAR Point Clouds","created":"2022-07-04","cited_by_count":29},{"id":"2003.13834","title":"Label-Efficient Learning on Point Clouds using Approximate Convex Decompositions","created":"2020-03-30","cited_by_count":27},{"id":"2109.06619","title":"Sampling Network Guided Cross-Entropy Method for Unsupervised Point Cloud Registration","created":"2021-09-14","cited_by_count":24},{"id":"2303.11610","title":"Novel Class Discovery for 3D Point Cloud Semantic Segmentation","created":"2023-03-21","cited_by_count":21},{"id":"2112.05213","title":"Progressive Seed Generation Auto-encoder for Unsupervised Point Cloud Learning","created":"2021-12-09","cited_by_count":12},{"id":"2210.09836","title":"Overlap-guided Gaussian Mixture Models for Point Cloud Registration","created":"2022-10-17","cited_by_count":10},{"id":"2203.05380","title":"Spatial Commonsense Graph for Object Localisation in Partial Scenes","created":"2022-03-10","cited_by_count":9},{"id":"2210.02798","title":"Data Augmentation-free Unsupervised Learning for 3D Point Cloud Understanding","created":"2022-10-06","cited_by_count":6}],"next_cursor":null}