论文信息 - Semantic Segmentation of Aerial Images Using Binary Space Partitioning - 字舞流文

Semantic Segmentation of Aerial Images Using Binary Space Partitioning

Jörn Ostermann | Daniel Gritzner

[1] Jairo Alejandro Gomez,et al. Spatiotemporal Modeling of Urban Growth Using Machine Learning , 2019, Remote. Sens..

[2] Henry Fuchs,et al. On visible surface generation by a priori tree structures , 1980, SIGGRAPH '80.

[3] Wei Liu,et al. Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images , 2018, ECCV.

[4] George Papandreou,et al. Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation , 2018, ECCV.

[5] Thomas Brox,et al. 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation , 2016, MICCAI.

[6] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.

[7] Kwon Lee,et al. Classification of Landscape Affected by Deforestation Using High-Resolution Remote Sensing Data and Deep-Learning Techniques , 2020, Remote. Sens..

[8] Guillaume Charpiat,et al. Aligning and Updating Cadaster Maps with Aerial Images by Multi-task, Multi-resolution Deep Learning , 2018, ACCV.

[9] Iasonas Kokkinos,et al. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.