- Tsinghua UniversityCN1.1k papers
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53 papers · 2 filters
Hi-UCD: A Large-scale Dataset for Urban Semantic Change Detection in Remote Sensing Imagery
Shiqi Tian, Ailong Ma, Zhuo Zheng +1
With the acceleration of the urban expansion, urban change detection (UCD), as a significant and effective approach, can provide the change information with respect to geospatial o…
Multi-Head Linear Attention Generative Adversarial Network for Thin Cloud Removal
Chenxi Duan, Rui Li
In remote sensing images, the existence of the thin cloud is an inevitable and ubiquitous phenomenon that crucially reduces the quality of imageries and limits the scenarios of app…
FG-Net: Fast Large-Scale LiDAR Point Clouds Understanding Network Leveraging Correlated Feature Mining and Geometric-Aware Modelling
Kangcheng Liu, Zhi Gao, Feng Lin +1
This work presents FG-Net, a general deep learning framework for large-scale point clouds understanding without voxelizations, which achieves accurate and real-time performance wit…
Multi-stage Attention ResU-Net for Semantic Segmentation of Fine-Resolution Remote Sensing Images
Rui Li, Shunyi Zheng, Chenxi Duan +2
The attention mechanism can refine the extracted feature maps and boost the classification performance of the deep network, which has become an essential technique in computer visi…
Learning geometry-image representation for 3D point cloud generation
Lei Wang, Yuchun Huang, Pengjie Tao +2
We study the problem of generating point clouds of 3D objects. Instead of discretizing the object into 3D voxels with huge computational cost and resolution limitations, we propose…
FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification
Zhuo Zheng, Yanfei Zhong, Ailong Ma +1
Deep learning techniques have provided significant improvements in hyperspectral image (HSI) classification. The current deep learning based HSI classifiers follow a patch-based le…