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Papers (including subtopics)

PIDForest: Anomaly Detection via Partial Identification NeurIPS 2019 PIE: A Large-Scale Dataset and Models for Pedestrian Intention Estimation and Trajectory Prediction ICCV 2019 PIEs: Pose Invariant Embeddings CVPR 2019 PifPaf: Composite Fields for Human Pose Estimation CVPR 2019 PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization ICCV 2019 Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimation ICCV 2019 Pix2Vox: Context-Aware 3D Reconstruction From Single and Multi-View Images ICCV 2019 Pixel2Mesh++: Multi-View 3D Mesh Generation via Deformation ICCV 2019 PlaneRCNN: 3D Plane Detection and Reconstruction From a Single Image CVPR 2019 PLMP - Point-Line Minimal Problems in Complete Multi-View Visibility ICCV 2019 POD: Practical Object Detection With Scale-Sensitive Network ICCV 2019 Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-Based Sequence to Sequence Network AAAI 2019 Point-Based Multi-View Stereo Network ICCV 2019 Point Cloud Oversegmentation With Graph-Structured Deep Metric Learning CVPR 2019 Point Cloud Processing via Recurrent Set Encoding AAAI 2019 PointCloud Saliency Maps ICCV 2019 PointConv: Deep Convolutional Networks on 3D Point Clouds CVPR 2019 PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation NeurIPS 2019 PointFlowNet: Learning Representations for Rigid Motion Estimation From Point Clouds CVPR 2019 PointNetLK: Robust & Efficient Point Cloud Registration Using PointNet CVPR 2019 PointPillars: Fast Encoders for Object Detection From Point Clouds CVPR 2019 PointRCNN: 3D Object Proposal Generation and Detection From Point Cloud CVPR 2019 Point-To-Pose Voting Based Hand Pose Estimation Using Residual Permutation Equivariant Layer CVPR 2019 Point-Voxel CNN for Efficient 3D Deep Learning NeurIPS 2019 PointWeb: Enhancing Local Neighborhood Features for Point Cloud Processing CVPR 2019