Large-Scale Semantic 3-D Reconstruction: Outcome of the 2019 IEEE GRSS Data Fusion Contest—Part A
暂无分享,去创建一个
Naoto Yokoya | Gregory D. Hager | Hongyu Chen | Seyed Majid Azimi | Pablo d'Angelo | Ronny Hänsch | Daniele Cerra | Myron Z. Brown | Hongyan Zhang | Bertrand Le Saux | Manhui Lin | Saket Kunwar | Gregory Hager | Hongyan Zhang | N. Yokoya | D. Cerra | P. d’Angelo | B. L. Saux | R. Hänsch | S. Azimi | Saket Kunwar | M. Brown | Manhui Lin | Hongyu Chen
[1] Zhengyang Wang,et al. Smoothed dilated convolutions for improved dense prediction , 2018, Data Mining and Knowledge Discovery.
[2] George Papandreou,et al. Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation , 2018, ECCV.
[3] Gordon Christie,et al. Learning Geocentric Object Pose in Oblique Monocular Images , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[4] Pietro Perona,et al. Fast Feature Pyramids for Object Detection , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[5] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[6] Yong-Sheng Chen,et al. Pyramid Stereo Matching Network , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[7] Qian Du,et al. Hyperspectral and LiDAR Data Fusion: Outcome of the 2013 GRSS Data Fusion Contest , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[8] Ross B. Girshick,et al. Focal Loss for Dense Object Detection , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[9] Alexandre Boulch,et al. Processing of Extremely High-Resolution LiDAR and RGB Data: Outcome of the 2015 IEEE GRSS Data Fusion Contest–Part A: 2-D Contest , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[10] Naoto Yokoya,et al. Large-Scale Semantic 3-D Reconstruction: Outcome of the 2019 IEEE GRSS Data Fusion Contest—Part B , 2021, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[11] S. K. McFeeters. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features , 1996 .
[12] Geoffrey E. Hinton,et al. On the importance of initialization and momentum in deep learning , 2013, ICML.
[13] Mathias Schardt,et al. Advanced DTM Generation from Very High Resolution Satellite Stereo Images , 2015 .
[14] Qian Du,et al. Multi-Modal Change Detection, Application to the Detection of Flooded Areas: Outcome of the 2009–2010 Data Fusion Contest , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[15] Hongyan Zhang,et al. Multi-Level Fusion of the Multi-Receptive Fields Contextual Networks and Disparity Network for Pairwise Semantic Stereo , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.
[16] Yanfei Zhong,et al. Pop-Net: Encoder-Dual Decoder for Semantic Segmentation and Single-View Height Estimation , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.
[17] Heiko Hirschmüller,et al. Stereo Processing by Semiglobal Matching and Mutual Information , 2008, IEEE Trans. Pattern Anal. Mach. Intell..
[18] Wei Liu,et al. Pairwise Stereo Image Disparity and Semantics Estimation with the Combination of U-Net and Pyramid Stereo Matching Network , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.
[19] SSC Satimage,et al. Precision Rectification of SPOT Imagery , 2007 .
[20] Aleksandra Pizurica,et al. Processing of Multiresolution Thermal Hyperspectral and Digital Color Data: Outcome of the 2014 IEEE GRSS Data Fusion Contest , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[21] Rowel Atienza,et al. Fast Disparity Estimation Using Dense Networks , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[22] Gregory D. Hager,et al. Semantic Stereo for Incidental Satellite Images , 2018, 2019 IEEE Winter Conference on Applications of Computer Vision (WACV).
[23] Saket Kunwar. U-Net Ensemble for Semantic and Height Estimation Using Coarse-Map Initialization , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.
[24] Naoto Yokoya,et al. Advanced Multi-Sensor Optical Remote Sensing for Urban Land Use and Land Cover Classification: Outcome of the 2018 IEEE GRSS Data Fusion Contest , 2019, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[25] Pablo d'Angelo,et al. Dense multi-view stereo from satellite imagery , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.
[26] Aloysius Wehr,et al. Airborne laser scanning—an introduction and overview , 1999 .
[27] Rob Fergus,et al. Depth Map Prediction from a Single Image using a Multi-Scale Deep Network , 2014, NIPS.
[28] Kilian Q. Weinberger,et al. Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[29] Naoto Yokoya,et al. Open Data for Global Multimodal Land Use Classification: Outcome of the 2017 IEEE GRSS Data Fusion Contest , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[30] Jocelyn Chanussot,et al. Decision Fusion for the Classification of Hyperspectral Data: Outcome of the 2008 GRS-S Data Fusion Contest , 2009, IEEE Transactions on Geoscience and Remote Sensing.
[31] Gabriele Moser,et al. Processing of Extremely High Resolution LiDAR and RGB Data: Outcome of the 2015 IEEE GRSS Data Fusion Contest—Part B: 3-D Contest , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[32] Nikos Paragios,et al. Multitemporal Very High Resolution From Space: Outcome of the 2016 IEEE GRSS Data Fusion Contest , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[33] Wei Liu,et al. Semantic 3D Reconstruction Using Multi-View High-Resolution Satellite Images Based on U-Net and Image-Guided Depth Fusion , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.
[34] Thierry Toutin,et al. Review of developments in geometric modelling for high resolution satellite pushbroom sensors , 2012 .
[35] Xiaojuan Qi,et al. ICNet for Real-Time Semantic Segmentation on High-Resolution Images , 2017, ECCV.
[36] Jocelyn Chanussot,et al. Comparison of Pansharpening Algorithms: Outcome of the 2006 GRS-S Data-Fusion Contest , 2007, IEEE Transactions on Geoscience and Remote Sensing.
[37] Seyed Majid Azimi,et al. 3D Semantic Segmentation from Multi-View Optical Satellite Images , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.
[38] William J. Emery,et al. Urban Mapping Using Coarse SAR and Optical Data: Outcome of the 2007 GRSS Data Fusion Contest , 2008, IEEE Geoscience and Remote Sensing Letters.
[39] Pablo d'Angelo. Automatic Orientation of large multitemporal Satellite Image Blocks , 2013 .
[40] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[41] Enhua Wu,et al. Squeeze-and-Excitation Networks , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[42] Marc Bosch,et al. A multiple view stereo benchmark for satellite imagery , 2016, 2016 IEEE Applied Imagery Pattern Recognition Workshop (AIPR).
[43] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[44] Xiangyu Zhang,et al. Large Kernel Matters — Improve Semantic Segmentation by Global Convolutional Network , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[45] Zhang Li,et al. AUTOMATIC DSM GENERATION FROM LINEAR ARRAY IMAGERY DATA , 2004 .
[46] Qian Du,et al. Multi-Modal and Multi-Temporal Data Fusion: Outcome of the 2012 GRSS Data Fusion Contest , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[47] Enric Meinhardt,et al. Automatic 3D Reconstruction from Multi-date Satellite Images , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[48] Foreword to the Special Issue on Optical Multiangular Data Exploitation and Outcome of the 2011 GRSS Data Fusion Contest , 2012 .
[49] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).