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.
1 code implementation • 29 Oct 2023 • Zhen Qian, Min Chen, Zhuo Sun, Fan Zhang, Qingsong Xu, Jinzhao Guo, Zhiwei Xie, Zhixin Zhang
Understanding urban dynamics and promoting sustainable development requires comprehensive insights about buildings.
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.
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 • 16 Jun 2023 • Qingsong Xu, Yilei Shi, Xiao Xiang Zhu
It consists of two stages, space granulation and attribute granulation.
2 code implementations • 7 Apr 2023 • Xiaoming Zhao, Xingming Wu, Weihai Chen, Peter C. Y. Chen, Qingsong Xu, Zhengguo Li
Image keypoints and descriptors play a crucial role in many visual measurement tasks.
no code implementations • 7 Mar 2023 • Bochen Xie, Yongjian Deng, Zhanpeng Shao, Hai Liu, Qingsong Xu, Youfu Li
To fit the sparse nature of events and sufficiently explore the relationship between them, we develop a novel attention-aware model named Event Voxel Set Transformer (EVSTr) for spatiotemporal representation learning on event streams.
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.
no code implementations • 20 Aug 2020 • Qingsong Xu, Xin Yuan, Chaojun Ouyang, Yue Zeng
First, a novel segmentation framework, called the heavy-weight spatial feature fusion pyramid network (FFPNet), is proposed to address the spatial problem of high-resolution remote sensing images.
1 code implementation • 28 Aug 2019 • Qingsong Xu, Chaojun Ouyang, Tianhai Jiang, Xuanmei Fan, Duoxiang Cheng
Automatic recognition and segmentation methods now become the essential requirement in identifying co-seismic landslides, which are fundamental for disaster assessment and mitigation in large-scale earthquakes.