{"list":"other","total":85,"rows":[{"id":"1506.01497","title":"Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks","created":"2015-06-04","cited_by_count":9639},{"id":"2005.12872","title":"End-to-End Object Detection with Transformers","created":"2020-05-26","cited_by_count":7414},{"id":"1703.06870","title":"Mask R-CNN","created":"2017-03-20","cited_by_count":7277},{"id":"1612.00593","title":"PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation","created":"2016-12-02","cited_by_count":5248},{"id":"1612.03144","title":"Feature Pyramid Networks for Object Detection","created":"2016-12-09","cited_by_count":5036},{"id":"1506.02640","title":"You Only Look Once: Unified, Real-Time Object Detection","created":"2015-06-08","cited_by_count":4852},{"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":"1512.02325","title":"SSD: Single Shot MultiBox Detector","created":"2015-12-08","cited_by_count":3130},{"id":"1504.08083","title":"Fast R-CNN","created":"2015-04-30","cited_by_count":2933},{"id":"1912.04838","title":"Scalability in Perception for Autonomous Driving: Waymo Open Dataset","created":"2019-12-10","cited_by_count":2451},{"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":"1904.01355","title":"FCOS: Fully Convolutional One-Stage Object Detection","created":"2019-04-02","cited_by_count":1577},{"id":"1612.08242","title":"YOLO9000: Better, Faster, Stronger","created":"2016-12-25","cited_by_count":1431},{"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":"1712.00726","title":"Cascade R-CNN: Delving into High Quality Object Detection","created":"2017-12-03","cited_by_count":1276},{"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":"1904.07850","title":"Objects as Points","created":"2019-04-16","cited_by_count":1175},{"id":"2006.11275","title":"Center-based 3D Object Detection and Tracking","created":"2020-06-19","cited_by_count":1144},{"id":"2008.05711","title":"Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3D","created":"2020-08-13","cited_by_count":1044},{"id":"1812.04244","title":"PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud","created":"2018-12-11","cited_by_count":941},{"id":"1912.13192","title":"PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection","created":"2019-12-31","cited_by_count":891},{"id":"1801.07791","title":"PointCNN: Convolution On $\\mathcal{X}$-Transformed Points","created":"2018-01-23","cited_by_count":764},{"id":"1808.01244","title":"CornerNet: Detecting Objects as Paired Keypoints","created":"2018-08-03","cited_by_count":763},{"id":"1711.10275","title":"3D Semantic Segmentation with Submanifold Sparse Convolutional Networks","created":"2017-11-28","cited_by_count":748},{"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":"1904.08189","title":"CenterNet: Keypoint Triplets for Object Detection","created":"2019-04-17","cited_by_count":654},{"id":"1904.09664","title":"Deep Hough Voting for 3D Object Detection in Point Clouds","created":"2019-04-21","cited_by_count":648},{"id":"1711.08488","title":"Frustum PointNets for 3D Object Detection from RGB-D Data","created":"2017-11-22","cited_by_count":640},{"id":"1901.07518","title":"Hybrid Task Cascade for Instance Segmentation","created":"2019-01-22","cited_by_count":481},{"id":"1812.07179","title":"Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving","created":"2018-12-18","cited_by_count":457},{"id":"1911.10150","title":"PointPainting: Sequential Fusion for 3D Object Detection","created":"2019-11-22","cited_by_count":449},{"id":"2002.10187","title":"3DSSD: Point-based 3D Single Stage Object Detector","created":"2020-02-24","cited_by_count":440},{"id":"1605.06409","title":"R-FCN: Object Detection via Region-based Fully Convolutional Networks","created":"2016-05-20","cited_by_count":414},{"id":"2012.15712","title":"Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection","created":"2020-12-31","cited_by_count":410},{"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":"1902.06326","title":"PIXOR: Real-time 3D Object Detection from Point Clouds","created":"2019-02-17","cited_by_count":358},{"id":"1908.09492","title":"Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection","created":"2019-08-26","cited_by_count":350},{"id":"1907.03739","title":"Point-Voxel CNN for Efficient 3D Deep Learning","created":"2019-07-08","cited_by_count":343},{"id":"2003.01251","title":"Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud","created":"2020-03-02","cited_by_count":335},{"id":"1712.02294","title":"Joint 3D Proposal Generation and Object Detection from View Aggregation","created":"2017-12-06","cited_by_count":326},{"id":"1907.10471","title":"STD: Sparse-to-Dense 3D Object Detector for Point Cloud","created":"2019-07-22","cited_by_count":282},{"id":"1612.00496","title":"3D Bounding Box Estimation Using Deep Learning and Geometry","created":"2016-12-01","cited_by_count":278},{"id":"1904.11490","title":"RepPoints: Point Set Representation for Object Detection","created":"2019-04-25","cited_by_count":264},{"id":"2012.10992","title":"Deep Continuous Fusion for Multi-Sensor 3D Object Detection","created":"2020-12-20","cited_by_count":263},{"id":"1904.02701","title":"Libra R-CNN: Towards Balanced Learning for Object Detection","created":"2019-04-04","cited_by_count":255},{"id":"1907.06038","title":"M3D-RPN: Monocular 3D Region Proposal Network for Object Detection","created":"2019-07-13","cited_by_count":252},{"id":"1706.01307","title":"Submanifold Sparse Convolutional Networks","created":"2017-06-05","cited_by_count":223},{"id":"2012.12397","title":"Multi-Task Multi-Sensor Fusion for 3D Object Detection","created":"2020-12-22","cited_by_count":203},{"id":"1906.06310","title":"Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving","created":"2019-06-14","cited_by_count":188},{"id":"2004.12636","title":"3D-CVF: Generating Joint Camera and LiDAR Features Using Cross-View Spatial Feature Fusion for 3D Object Detection","created":"2020-04-27","cited_by_count":176},{"id":"1910.06528","title":"End-to-End Multi-View Fusion for 3D Object Detection in LiDAR Point Clouds","created":"2019-10-15","cited_by_count":171},{"id":"2007.08856","title":"EPNet: Enhancing Point Features with Image Semantics for 3D Object Detection","created":"2020-07-17","cited_by_count":164},{"id":"1902.09738","title":"Stereo R-CNN based 3D Object Detection for Autonomous Driving","created":"2019-02-26","cited_by_count":163},{"id":"1802.08275","title":"SPLATNet: Sparse Lattice Networks for Point Cloud Processing","created":"2018-02-22","cited_by_count":158},{"id":"1901.08043","title":"Bottom-up Object Detection by Grouping Extreme and Center Points","created":"2019-01-23","cited_by_count":156},{"id":"2001.03343","title":"RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving","created":"2020-01-10","cited_by_count":150},{"id":"2009.00784","title":"CLOCs: Camera-LiDAR Object Candidates Fusion for 3D Object Detection","created":"2020-09-02","cited_by_count":147},{"id":"2007.10323","title":"Pillar-based Object Detection for Autonomous Driving","created":"2020-07-20","cited_by_count":137},{"id":"1903.08701","title":"LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving","created":"2019-03-20","cited_by_count":133},{"id":"1908.03851","title":"IoU Loss for 2D/3D Object Detection","created":"2019-08-11","cited_by_count":128},{"id":"1903.01864","title":"Frustum ConvNet: Sliding Frustums to Aggregate Local Point-Wise Features for Amodal 3D Object Detection","created":"2019-03-05","cited_by_count":124},{"id":"1812.02781","title":"ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape","created":"2018-12-06","cited_by_count":123},{"id":"1908.02990","title":"Fast Point R-CNN","created":"2019-08-08","cited_by_count":119},{"id":"1811.05181","title":"Gradient Harmonized Single-stage Detector","created":"2018-11-13","cited_by_count":114},{"id":"1511.02300","title":"Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images","created":"2015-11-07","cited_by_count":111},{"id":"1903.10955","title":"GS3D: An Efficient 3D Object Detection Framework for Autonomous Driving","created":"2019-03-26","cited_by_count":106},{"id":"1912.02984","title":"Grid-GCN for Fast and Scalable Point Cloud Learning","created":"2019-12-06","cited_by_count":103},{"id":"2001.03398","title":"DSGN: Deep Stereo Geometry Network for 3D Object Detection","created":"2020-01-10","cited_by_count":101},{"id":"1703.07570","title":"Deep MANTA: A Coarse-to-fine Many-Task Network for joint 2D and 3D vehicle analysis from monocular image","created":"2017-03-22","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":"1912.12791","title":"Object as Hotspots: An Anchor-Free 3D Object Detection Approach via Firing of Hotspots","created":"2019-12-30","cited_by_count":84},{"id":"1802.04402","title":"Recurrent Slice Networks for 3D Segmentation of Point Clouds","created":"2018-02-13","cited_by_count":82},{"id":"2003.00186","title":"HVNet: Hybrid Voxel Network for LiDAR Based 3D Object Detection","created":"2020-02-29","cited_by_count":82},{"id":"2004.03080","title":"End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection","created":"2020-04-07","cited_by_count":80},{"id":"2012.11704","title":"HDNET: Exploiting HD Maps for 3D Object Detection","created":"2020-12-21","cited_by_count":78},{"id":"1909.13603","title":"Multi-view PointNet for 3D Scene Understanding","created":"2019-09-30","cited_by_count":76},{"id":"1909.10469","title":"Hierarchical Point-Edge Interaction Network for Point Cloud Semantic Segmentation","created":"2019-09-23","cited_by_count":68},{"id":"1509.04874","title":"DenseBox: Unifying Landmark Localization with End to End Object Detection","created":"2015-09-16","cited_by_count":58},{"id":"1908.11069","title":"StarNet: Targeted Computation for Object Detection in Point Clouds","created":"2019-08-29","cited_by_count":46},{"id":"1901.03495","title":"FishNet: A Versatile Backbone for Image, Region, and Pixel Level Prediction","created":"2019-01-11","cited_by_count":16},{"id":"1907.05286","title":"Voxel-FPN: multi-scale voxel feature aggregation in 3D object detection from point clouds","created":"2019-06-28","cited_by_count":9},{"id":"1504.02764","title":"A Coarse-to-Fine Model for 3D Pose Estimation and Sub-category Recognition","created":"2015-04-10","cited_by_count":4}],"next_cursor":null}