3.2k citations · 10k across the 87 of their papers we have counts for
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Cross-City Matters: A Multimodal Remote Sensing Benchmark Dataset for Cross-City Semantic Segmentation using High-Resolution Domain Adaptation Networks
Danfeng Hong, Bing Zhang, Hao Li +7
Artificial intelligence (AI) approaches nowadays have gained remarkable success in single-modality-dominated remote sensing (RS) applications, especially with an emphasis on indivi…
HTC-DC Net: Monocular Height Estimation from Single Remote Sensing Images
Sining Chen, Yilei Shi, Zhitong Xiong +1
3D geo-information is of great significance for understanding the living environment; however, 3D perception from remote sensing data, especially on a large scale, is restricted. T…
Self-supervised Domain-agnostic Domain Adaptation for Satellite Images
Fahong Zhang, Yilei Shi, Xiao Xiang Zhu
Domain shift caused by, e.g., different geographical regions or acquisition conditions is a common issue in machine learning for global scale satellite image processing. A promisin…
Few-shot Object Detection in Remote Sensing: Lifting the Curse of Incompletely Annotated Novel Objects
Fahong Zhang, Yilei Shi, Zhitong Xiong +1
Object detection is an essential and fundamental task in computer vision and satellite image processing. Existing deep learning methods have achieved impressive performance thanks…
Decoupling Common and Unique Representations for Multimodal Self-supervised Learning
Yi Wang, Conrad M Albrecht, Nassim Ait Ali Braham +3
The increasing availability of multi-sensor data sparks wide interest in multimodal self-supervised learning. However, most existing approaches learn only common representations ac…
High Quality Large-Scale 3-D Urban Mapping with Multi-Master TomoSAR
Yilei Shi, Richard Bamler, Yuanyuan Wang +1
Multi-baseline interferometric synthetic aperture radar (InSAR) techniques are effective approaches for retrieving the 3-D information of urban areas. In order to obtain a plausibl…
Enabling Country-Scale Land Cover Mapping with Meter-Resolution Satellite Imagery
Xin-Yi Tong, Gui-Song Xia, Xiao Xiang Zhu
High-resolution satellite images can provide abundant, detailed spatial information for land cover classification, which is particularly important for studying the complicated buil…
Monitoring Urban Forests from Auto-Generated Segmentation Maps
Conrad M Albrecht, Chenying Liu, Yi Wang +2
We present and evaluate a weakly-supervised methodology to quantify the spatio-temporal distribution of urban forests based on remotely sensed data with close-to-zero human interac…
GLF-CR: SAR-Enhanced Cloud Removal with Global-Local Fusion
Fang Xu, Yilei Shi, Patrick Ebel +4
The challenge of the cloud removal task can be alleviated with the aid of Synthetic Aperture Radar (SAR) images that can penetrate cloud cover. However, the large domain gap betwee…
Self-supervised Vision Transformers for Joint SAR-optical Representation Learning
Yi Wang, Conrad M Albrecht, Xiao Xiang Zhu
Self-supervised learning (SSL) has attracted much interest in remote sensing and earth observation due to its ability to learn task-agnostic representations without human annotatio…
Disentangled Latent Transformer for Interpretable Monocular Height Estimation
Zhitong Xiong, Sining Chen, Yilei Shi +1
Monocular height estimation (MHE) from remote sensing imagery has high potential in generating 3D city models efficiently for a quick response to natural disasters. Most existing w…
Multimodal Remote Sensing Benchmark Datasets for Land Cover Classification with A Shared and Specific Feature Learning Model
Danfeng Hong, Jingliang Hu, Jing Yao +2
As remote sensing (RS) data obtained from different sensors become available largely and openly, multimodal data processing and analysis techniques have been garnering increasing i…
Generative modeling of spatio-temporal weather patterns with extreme event conditioning
Konstantin Klemmer, Sudipan Saha, Matthias Kahl +2
Deep generative models are increasingly used to gain insights in the geospatial data domain, e.g., for climate data. However, most existing approaches work with temporal snapshots…
Aerial Scene Understanding in The Wild: Multi-Scene Recognition via Prototype-based Memory Networks
Yuansheng Hua, Lichao Moua, Jianzhe Lin +2
Aerial scene recognition is a fundamental visual task and has attracted an increasing research interest in the last few years. Most of current researches mainly deploy efforts to c…
Towards a Collective Agenda on AI for Earth Science Data Analysis
Devis Tuia, Ribana Roscher, Jan Dirk Wegner +3
In the last years we have witnessed the fields of geosciences and remote sensing and artificial intelligence to become closer. Thanks to both the massive availability of observatio…
MultiScene: A Large-scale Dataset and Benchmark for Multi-scene Recognition in Single Aerial Images
Yuansheng Hua, Lichao Mou, Pu Jin +1
Aerial scene recognition is a fundamental research problem in interpreting high-resolution aerial imagery. Over the past few years, most studies focus on classifying an image into…
HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline
Konrad Heidler, Lichao Mou, Celia Baumhoer +2
Deep learning-based coastline detection algorithms have begun to outshine traditional statistical methods in recent years. However, they are usually trained only as single-purpose…
Interpretable Hyperspectral AI: When Non-Convex Modeling meets Hyperspectral Remote Sensing
Danfeng Hong, Wei He, Naoto Yokoya +5
Hyperspectral imaging, also known as image spectrometry, is a landmark technique in geoscience and remote sensing (RS). In the past decade, enormous efforts have been made to proce…
Self-Supervised Multisensor Change Detection
Sudipan Saha, Patrick Ebel, Xiao Xiang Zhu
Most change detection methods assume that pre-change and post-change images are acquired by the same sensor. However, in many real-life scenarios, e.g., natural disaster, it is mor…
Adversarial Shape Learning for Building Extraction in VHR Remote Sensing Images
Lei Ding, Hao Tang, Yahui Liu +3
Building extraction in VHR RSIs remains a challenging task due to occlusion and boundary ambiguity problems. Although conventional convolutional neural networks (CNNs) based method…
Semantic Segmentation of Remote Sensing Images with Sparse Annotations
Yuansheng Hua, Diego Marcos, Lichao Mou +2
Training Convolutional Neural Networks (CNNs) for very high resolution images requires a large quantity of high-quality pixel-level annotations, which is extremely labor- and time-…
Exploring Deep 3D Spatial Encodings for Large-Scale 3D Scene Understanding
Saqib Ali Khan, Yilei Shi, Muhammad Shahzad +1
Semantic segmentation of raw 3D point clouds is an essential component in 3D scene analysis, but it poses several challenges, primarily due to the non-Euclidean nature of 3D point…
Multi-task Learning for Human Settlement Extent Regression and Local Climate Zone Classification
Chunping Qiu, Lukas Liebel, Lloyd H. Hughes +3
Human Settlement Extent (HSE) and Local Climate Zone (LCZ) maps are both essential sources, e.g., for sustainable urban development and Urban Heat Island (UHI) studies. Remote sens…
A Novel Actor Dual-Critic Model for Remote Sensing Image Captioning
Ruchika Chavhan, Biplab Banerjee, Xiao Xiang Zhu +1
We deal with the problem of generating textual captions from optical remote sensing (RS) images using the notion of deep reinforcement learning. Due to the high inter-class similar…