3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans
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Matthias Nießner | Angela Dai | Ji Hou | M. Nießner | Angela Dai | Ji Hou
[1] Leonidas J. Guibas,et al. GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[2] Vladlen Koltun,et al. Tangent Convolutions for Dense Prediction in 3D , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[3] Matthias Nießner,et al. 3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation , 2018, ECCV.
[4] Marc Levoy,et al. A volumetric method for building complex models from range images , 1996, SIGGRAPH.
[5] Subhransu Maji,et al. Multi-view Convolutional Neural Networks for 3D Shape Recognition , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[6] Matthias Nießner,et al. Matterport3D: Learning from RGB-D Data in Indoor Environments , 2017, 2017 International Conference on 3D Vision (3DV).
[7] Leonidas J. Guibas,et al. Frustum PointNets for 3D Object Detection from RGB-D Data , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[8] Jianxiong Xiao,et al. Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Eugenio Culurciello,et al. ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation , 2016, ArXiv.
[10] Ulrich Neumann,et al. SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[11] Leonidas J. Guibas,et al. Volumetric and Multi-view CNNs for Object Classification on 3D Data , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Matthias Nießner,et al. ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[13] Trevor Darrell,et al. Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[14] Thomas A. Funkhouser,et al. Semantic Scene Completion from a Single Depth Image , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[15] Carsten Rother,et al. Panoptic Segmentation , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Wei Liu,et al. SSD: Single Shot MultiBox Detector , 2015, ECCV.
[17] Jianxiong Xiao,et al. Sliding Shapes for 3D Object Detection in Depth Images , 2014, ECCV.
[18] Kaiming He,et al. Focal Loss for Dense Object Detection , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[19] Matthias Nießner,et al. Shape Completion Using 3D-Encoder-Predictor CNNs and Shape Synthesis , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Leonidas J. Guibas,et al. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[21] Leonidas J. Guibas,et al. ShapeNet: An Information-Rich 3D Model Repository , 2015, ArXiv.
[22] Leonidas J. Guibas,et al. PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space , 2017, NIPS.
[23] Ross B. Girshick,et al. Fast R-CNN , 2015, 1504.08083.
[24] Jianxiong Xiao,et al. 3D ShapeNets: A deep representation for volumetric shapes , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Jianxiong Xiao,et al. SUN RGB-D: A RGB-D scene understanding benchmark suite , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[26] Gernot Riegler,et al. OctNet: Learning Deep 3D Representations at High Resolutions , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[27] Matthias Nießner,et al. BundleFusion , 2016, TOGS.
[28] Kaiming He,et al. Feature Pyramid Networks for Object Detection , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[29] Forrest N. Iandola,et al. DenseNet: Implementing Efficient ConvNet Descriptor Pyramids , 2014, ArXiv.
[30] Subhransu Maji,et al. 3D Shape Segmentation with Projective Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[31] Matthias Nießner,et al. ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Ali Farhadi,et al. You Only Look Once: Unified, Real-Time Object Detection , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Silvio Savarese,et al. Joint 2D-3D-Semantic Data for Indoor Scene Understanding , 2017, ArXiv.
[34] Sebastian Scherer,et al. VoxNet: A 3D Convolutional Neural Network for real-time object recognition , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[35] Ross B. Girshick,et al. Focal Loss for Dense Object Detection , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[36] Bastian Leibe,et al. 3D-BEVIS: Birds-Eye-View Instance Segmentation , 2019, GCPR.
[37] Kaiming He,et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[38] Kaiming He,et al. Mask R-CNN , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).