21 citations · 46 across the 18 of their papers we have counts for
20 papers
EO-VAE: Towards A Multi-sensor Tokenizer for Earth Observation Data
Nils Lehmann, Yi Wang, Zhitong Xiong +1
State-of-the-art generative image and video models rely heavily on tokenizers that compress high-dimensional inputs into more efficient latent representations. While this paradigm…
Hierarchical Semi-Supervised Active Learning for Remote Sensing
Wei Huang, Zhitong Xiong, Chenying Liu +1
The performance of deep learning models in remote sensing (RS) strongly depends on the availability of high-quality labeled data. However, collecting large-scale annotations is cos…
ExEBench: Benchmarking Foundation Models on Extreme Earth Events
Shan Zhao, Zhitong Xiong, Jie Zhao +1
Our planet is facing increasingly frequent extreme events, which pose major risks to human lives and ecosystems. Recent advances in machine learning (ML), especially with foundatio…
REOBench: Benchmarking Robustness of Earth Observation Foundation Models
Xiang Li, Yong Tao, Siyuan Zhang +7
Earth observation foundation models have shown strong generalization across multiple Earth observation tasks, but their robustness under real-world perturbations remains underexplo…
GlobalGeoTree: A Multi-Granular Vision-Language Dataset for Global Tree Species Classification
Yang Mu, Zhitong Xiong, Yi Wang +5
Global tree species mapping using remote sensing data is vital for biodiversity monitoring, forest management, and ecological research. However, progress in this field has been con…
Towards a Unified Copernicus Foundation Model for Earth Vision
Yi Wang, Zhitong Xiong, Chenying Liu +8
Advances in Earth observation (EO) foundation models have unlocked the potential of big satellite data to learn generic representations from space, benefiting a wide range of downs…