Aug 2026· International Journal of Machine Learning and Cybernetics· Vol 17· 0 citations· 44 references
TL;DR
This work provides a robust and efficient novel approach for integrating generative models with physical constraints to achieve high-quality spatiotemporal forecasting.
Accurate short-term cloud motion forecasting is essential for applications such as weather nowcasting, aviation safety, renewable energy management, and disaster response, yet traditional numerical weather prediction models remain computationally intensive and limited in capturing fine-scale cloud dynamics. This paper...
P. Menon, Blaze Jose, Megha T. S. et al.· International Conference Inn...· 0 citations
The Cloud-Aware Wavelet Generative Adversarial Network (CLAW-GAN), a novel framework for high-fidelity reconstruction under cloud-contaminated conditions, achieves state-of-the-art performance and demonstrates superior robustness across varying cloud coverage.
Si-Chen Lu, Ming-Fei Li, Juan-Juan Jing et al.· Proceedings of the Thirty-Fi...· 0 citations
The findings indicate that CADE is precise and computationally efficient, showing that it is suitable for low-resource remote sensing uses and minimizes dependence on extensive annotated datasets as well.
Debopom Sutradhar, Md. Abdur Rahman, Kheng Cher Yeo et al.· Neural computing & applicati...· 0 citations
GeoFlow is a novel framework designed to achieve efficient driving video generation by harnessing explicit geometric priors, using a Geometry-Aligned Prior (GAP) distribution as starting point, and can achieve remarkable efficiency of both training and inference.
Jia-Zhen Liu, Hangbiao Li, J. Zhang et al.· 0 citations
Cloud removal is crucial for preprocessing optical remote sensing images affected by natural cloud contamination, which is highly diverse and variable. Clouds of varying thickness often occur simultaneously, where the boundary between these layers is ambiguous and hard to quantitatively define. Consequently, advanced d...
Yu-Jun Guo, Wei He, He Huang et al.· IEEE Transactions on Geoscie...· 0 citations
SpatialCrafter is presented, a novel two-stage framework that addresses explorable image-to-scene generation issues by introducing a global 3D proxy for high-fidelity image-to-scene generation and appearance refinement and introduces Parallel Geometry Injection and Proxy-Aware Corruption training strategies.
Chuan Fang, Lingteng Qiu, Yixun Liang et al.· 3 citations
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