no code implementations • 7 May 2024 • Xiao Xiang Zhu, Zhitong Xiong, Yi Wang, Adam J. Stewart, Konrad Heidler, Yuanyuan Wang, Zhenghang Yuan, Thomas Dujardin, Qingsong Xu, Yilei Shi
Foundation models have enormous potential in advancing Earth and climate sciences, however, current approaches may not be optimal as they focus on a few basic features of a desirable Earth and climate foundation model.
no code implementations • 22 Apr 2024 • Xiao Xiang Zhu, Qingyu Li, Yilei Shi, Yuanyuan Wang, Adam Stewart, Jonathan Prexl
Specifically, if solar panels were placed on the roofs of all buildings, they could supply 1. 1-3. 3 times -- depending on the efficiency of the solar device -- the global energy consumption in 2020, which is the year with the highest consumption on record.
1 code implementation • 18 Mar 2024 • Qingsong Xu, Yilei Shi, Jonathan Bamber, Chaojun Ouyang, Xiao Xiang Zhu
Large-scale hydrodynamic models generally rely on fixed-resolution spatial grids and model parameters as well as incurring a high computational cost.
no code implementations • 8 Oct 2023 • Qingsong Xu, Yilei Shi, Jonathan Bamber, Ye Tuo, Ralf Ludwig, Xiao Xiang Zhu
Specifically, we present a comprehensive review of the physics-aware ML methods, building a structured community (PaML) of existing methodologies that integrate prior physical knowledge or physics-based modeling into ML.
no code implementations • 28 Sep 2023 • Kun Qian, Yuanyuan Wang, Peter Jung, Yilei Shi, Xiao Xiang Zhu
Deep neural networks based on unrolled iterative algorithms have achieved remarkable success in sparse reconstruction applications, such as synthetic aperture radar (SAR) tomographic inversion (TomoSAR).
1 code implementation • 28 Sep 2023 • Sining Chen, Yilei Shi, Zhitong Xiong, Xiao Xiang Zhu
To tackle this problem, we propose a method for monocular height estimation from optical imagery, which is currently one of the richest sources of remote sensing data.
no code implementations • 20 Sep 2023 • Fahong Zhang, Yilei Shi, Xiao Xiang Zhu
A promising method to address this problem is domain adaptation, where the training and the testing datasets are split into two or multiple domains according to their distributions, and an adaptation method is applied to improve the generalizability of the model on the testing dataset.
1 code implementation • 19 Sep 2023 • Fahong Zhang, Yilei Shi, Zhitong Xiong, Xiao Xiang Zhu
In this context, few-shot object detection (FSOD) has emerged as a promising direction, which aims at enabling the model to detect novel objects with only few of them annotated.
1 code implementation • 2 Aug 2023 • Qingsong Xu, Yilei Shi, Jianhua Guo, Chaojun Ouyang, Xiao Xiang Zhu
Specifically, a transformer-driven image translation composed of a light-weight transformer and a domain-specific affinity weight is first proposed to mitigate domain shift between two images with real-time efficiency.
1 code implementation • 17 Jul 2023 • Zhaiyu Chen, Yilei Shi, Liangliang Nan, Zhitong Xiong, Xiao Xiang Zhu
We present PolyGNN, a polyhedron-based graph neural network for 3D building reconstruction from point clouds.
1 code implementation • 16 Jun 2023 • Qingsong Xu, Yilei Shi, Xiao Xiang Zhu
It consists of two stages, space granulation and attribute granulation.
no code implementations • 23 May 2023 • Kun Qian, Yuanyuan Wang, Peter Jung, Yilei Shi, Xiao Xiang Zhu
An emerging technique known as deep unrolling provided a good combination of the descriptive ability of neural networks, explainable, and computational efficiency for BPDN.
no code implementations • 8 May 2023 • Yilei Shi, Richard Bamler, Yuanyuan Wang, Xiao Xiang Zhu
Multi-baseline interferometric synthetic aperture radar (InSAR) techniques are effective approaches for retrieving the 3-D information of urban areas.
no code implementations • 8 May 2023 • Yilei Shi, Qinyu Li, Xiaoxiang Zhu
In this work, we have proposed a end-to-end framework to overcome this issue, which uses the graph convolutional network (GCN) for building footprint extraction task.
no code implementations • 29 Apr 2023 • Yifang Xu, Yunzhuo Sun, Yang Li, Yilei Shi, Xiaoxiang Zhu, Sidan Du
With the increasing demand for video understanding, video moment and highlight detection (MHD) has emerged as a critical research topic.
1 code implementation • 26 Jan 2023 • Qingsong Xu, Yilei Shi, Xin Yuan, Xiao Xiang Zhu
Empirical results show that the proposed model is effective and practical for remote sensing image scene classification, regardless of whether the source data is available or not.
1 code implementation • 9 Jan 2023 • Fang Xu, Yilei Shi, Patrick Ebel, Wen Yang, Xiao Xiang Zhu
In this paper, we introduce Planet-CR, a benchmark dataset for high-resolution cloud removal with multi-modal and multi-resolution data fusion.
no code implementations • 10 Oct 2022 • Zhitong Xiong, Fahong Zhang, Yi Wang, Yilei Shi, Xiao Xiang Zhu
Furthermore, a new platform for EO, termed EarthNets, is released to achieve a fair and consistent evaluation of deep learning methods on remote sensing data.
no code implementations • 6 Sep 2022 • Omid Ghorbanzadeh, Yonghao Xu, Hengwei Zhao, Junjue Wang, Yanfei Zhong, Dong Zhao, Qi Zang, Shuang Wang, Fahong Zhang, Yilei Shi, Xiao Xiang Zhu, Lin Bai, Weile Li, Weihang Peng, Pedram Ghamisi
The objective of the competition is to automatically detect landslides based on large-scale multiple sources of satellite imagery collected globally.
1 code implementation • 6 Jun 2022 • Fang Xu, Yilei Shi, Patrick Ebel, Lei Yu, Gui-Song Xia, Wen Yang, Xiao Xiang Zhu
The challenge of the cloud removal task can be alleviated with the aid of Synthetic Aperture Radar (SAR) images that can penetrate cloud cover.
Ranked #2 on Cloud Removal on SEN12MS-CR
no code implementations • 17 May 2022 • Qingyu Li, Yilei Shi, Xiao Xiang Zhu
Considering that rich information is also encoded in feature maps, we propose to integrate the consistency of both features and outputs in the end-to-end network training of unlabeled samples, enabling to impose additional constraints.
1 code implementation • 17 Jan 2022 • Zhitong Xiong, Sining Chen, Yilei Shi, Xiao Xiang Zhu
Furthermore, a novel unsupervised semantic segmentation task based on height estimation is first introduced in this work.
no code implementations • 8 Dec 2021 • Kun Qian, Yuanyuan Wang, Yilei Shi, Xiao Xiang Zhu
This superior performance comes at the cost of extra computational burdens, because of the sparse reconstruction, which cannot be solved analytically and we need to employ computationally expensive iterative solvers.
no code implementations • 22 Nov 2021 • Hasan Nasrallah, Abed Ellatif Samhat, Yilei Shi, Xiaoxiang Zhu, Ghaleb Faour, Ali J. Ghandour
Factors such as size, ground coverage ratio and PV_out are carefully investigated for each district.
1 code implementation • 22 Feb 2021 • Lei Ding, Hao Tang, Yahui Liu, Yilei Shi, Xiao Xiang Zhu, Lorenzo Bruzzone
To address this issue, we propose an adversarial shape learning network (ASLNet) to model the building shape patterns that improve the accuracy of building segmentation.
no code implementations • 29 Nov 2020 • Saqib Ali Khan, Yilei Shi, Muhammad Shahzad, Xiao Xiang Zhu
In this letter, we have proposed an alternative approach to overcome the limitations of CNN based approaches by encoding the spatial features of raw 3D point clouds into undirected symmetrical graph models.
no code implementations • 17 Jun 2020 • Xiao Xiang Zhu, Sina Montazeri, Mohsin Ali, Yuansheng Hua, Yuanyuan Wang, Lichao Mou, Yilei Shi, Feng Xu, Richard Bamler
Deep learning in remote sensing has become an international hype, but it is mostly limited to the evaluation of optical data.
no code implementations • 6 Jun 2020 • Qingyu Li, Lichao Mou, Yuansheng Hua, Yao Sun, Pu Jin, Yilei Shi, Xiao Xiang Zhu
The detected keypoints are subsequently reformulated as a closed polygon, which is the semantic boundary of the building.
no code implementations • 17 Mar 2020 • Yilei Shi, Richard Bamler, Yuanyuan Wang, Xiao Xiang Zhu
Multi-baseline interferometric synthetic aperture radar (InSAR) techniques are effective approaches for retrieving the 3-D information of urban areas.
no code implementations • 11 Feb 2020 • Qingyu Li, Yilei Shi, Xin Huang, Xiao Xiang Zhu
Due to the complexity of buildings, the accurate and reliable generation of the building footprint from remote sensing imagery is still a challenging task.
1 code implementation • 19 Dec 2019 • Xiao Xiang Zhu, Jingliang Hu, Chunping Qiu, Yilei Shi, Jian Kang, Lichao Mou, Hossein Bagheri, Matthias Häberle, Yuansheng Hua, Rong Huang, Lloyd Hughes, Hao Li, Yao Sun, Guichen Zhang, Shiyao Han, Michael Schmitt, Yuanyuan Wang
This is especially true for an automated analysis of remote sensing images on a global scale, which enables us to address global challenges such as urbanization and climate change using state-of-the-art machine learning techniques.
BIG-bench Machine Learning Cultural Vocal Bursts Intensity Prediction +1
no code implementations • 8 Nov 2019 • Yilei Shi, Qingyu Li, Xiao Xiang Zhu
Taking the semantic segmentation of building footprints as a practical example, we compared different feature embedding architectures and graph neural networks.
no code implementations • 5 Nov 2018 • Yilei Shi, Xiao Xiang Zhu, Richard Bamler
We propose to increase SNR by integrating non-local estimation into the inversion and show that a reasonable reconstruction of buildings from only seven interferograms is feasible.
no code implementations • 26 Oct 2018 • Yilei Shi, Qingyu Li, Xiao Xiang Zhu
The automatic generation of building footprints from satellite images presents a considerable challenge due to the complexity of building shapes.