CoReNet: Coherent 3D scene reconstruction from a single RGB image
暂无分享,去创建一个
Pablo Bauszat | Vittorio Ferrari | Stefan Popov | V. Ferrari | Pablo Bauszat | S. Popov | P. Bauszat
[1] Matthew B. Blaschko,et al. The Lovasz-Softmax Loss: A Tractable Surrogate for the Optimization of the Intersection-Over-Union Measure in Neural Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[2] Thomas Lewiner,et al. Efficient Implementation of Marching Cubes' Cases with Topological Guarantees , 2003, J. Graphics, GPU, & Game Tools.
[3] Silvio Savarese,et al. 3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction , 2016, ECCV.
[4] Hao Su,et al. A Point Set Generation Network for 3D Object Reconstruction from a Single Image , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Gordon Wetzstein,et al. DeepVoxels: Learning Persistent 3D Feature Embeddings , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Yaser Sheikh,et al. Neural volumes , 2019, ACM Trans. Graph..
[7] R. Venkatesh Babu,et al. 3D-LMNet: Latent Embedding Matching for Accurate and Diverse 3D Point Cloud Reconstruction from a Single Image , 2018, BMVC.
[8] Richard A. Newcombe,et al. DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Greg Humphreys,et al. Physically Based Rendering: From Theory to Implementation , 2004 .
[10] Thu Nguyen-Phuoc,et al. HoloGAN: Unsupervised Learning of 3D Representations From Natural Images , 2019, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW).
[11] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Thomas Brox,et al. What Do Single-View 3D Reconstruction Networks Learn? , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[13] Shangchen Zhou,et al. Pix2Vox++: Multi-scale Context-aware 3D Object Reconstruction from Single and Multiple Images , 2020, International Journal of Computer Vision.
[14] Derek Hoiem,et al. Pixels, Voxels, and Views: A Study of Shape Representations for Single View 3D Object Shape Prediction , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[15] C. Lawrence Zitnick,et al. Edge Boxes: Locating Object Proposals from Edges , 2014, ECCV.
[16] Thomas A. Funkhouser,et al. Semantic Scene Completion from a Single Depth Image , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[17] Stefan Leutenegger,et al. X-Section: Cross-Section Prediction for Enhanced RGB-D Fusion , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[18] Jiajun Wu,et al. Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[19] Xiaoguang Han,et al. Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes From a Single Image , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Sebastian Nowozin,et al. Occupancy Networks: Learning 3D Reconstruction in Function Space , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[21] Sébastien Ourselin,et al. Generalised Dice overlap as a deep learning loss function for highly unbalanced segmentations , 2017, DLMIA/ML-CDS@MICCAI.
[22] Hao Zhang,et al. BSP-Net: Generating Compact Meshes via Binary Space Partitioning , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Jun Li,et al. Im2Struct: Recovering 3D Shape Structure from a Single RGB Image , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[24] Alla Sheffer,et al. Front2Back: Single View 3D Shape Reconstruction via Front to Back Prediction , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Matthias Nießner,et al. Matterport3D: Learning from RGB-D Data in Indoor Environments , 2017, 2017 International Conference on 3D Vision (3DV).
[26] Yong-Liang Yang,et al. RenderNet: A deep convolutional network for differentiable rendering from 3D shapes , 2018, NeurIPS.
[27] Katerina Fragkiadaki,et al. Learning Spatial Common Sense With Geometry-Aware Recurrent Networks , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Leonidas J. Guibas,et al. Learning Shape Abstractions by Assembling Volumetric Primitives , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[29] Ross B. Girshick,et al. Mask R-CNN , 2017, 1703.06870.
[30] Wei Liu,et al. Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images , 2018, ECCV.
[31] Abhinav Gupta,et al. Learning a Predictable and Generative Vector Representation for Objects , 2016, ECCV.
[32] Jiajun Wu,et al. Synthesizing 3D Shapes via Modeling Multi-view Depth Maps and Silhouettes with Deep Generative Networks , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Krista A. Ehinger,et al. SUN database: Large-scale scene recognition from abbey to zoo , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[34] Mathieu Aubry,et al. A Papier-Mache Approach to Learning 3D Surface Generation , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[35] Jitendra Malik,et al. Mesh R-CNN , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[36] James M. Rehg,et al. 3D-RCNN: Instance-Level 3D Object Reconstruction via Render-and-Compare , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[37] Hao Li,et al. PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[38] Leonidas J. Guibas,et al. ShapeNet: An Information-Rich 3D Model Repository , 2015, ArXiv.
[39] Gordon Wetzstein,et al. Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations , 2019, NeurIPS.
[40] Jitendra Malik,et al. Learning a Multi-View Stereo Machine , 2017, NIPS.
[41] Yiyi Liao,et al. Deep Marching Cubes: Learning Explicit Surface Representations , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[42] Shengping Zhang,et al. Pix2Vox: Context-Aware 3D Reconstruction From Single and Multi-View Images , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[43] Jitendra Malik,et al. Factoring Shape, Pose, and Layout from the 2D Image of a 3D Scene , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[44] Ross B. Girshick,et al. Focal Loss for Dense Object Detection , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[45] Bernhard P. Wrobel,et al. Multiple View Geometry in Computer Vision , 2001 .
[46] Stefan Roth,et al. Matryoshka Networks: Predicting 3D Geometry via Nested Shape Layers , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[47] Hao Zhang,et al. Learning Implicit Fields for Generative Shape Modeling , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[48] Jiajun Wu,et al. Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling , 2016, NIPS.