9 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…
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…
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…
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…
Neural Plasticity-Inspired Multimodal Foundation Model for Earth Observation
Zhitong Xiong, Yi Wang, Fahong Zhang +7
Earth observation (EO) in open-world settings presents a unique challenge: different applications rely on diverse sensor modalities, each with varying ground sampling distances, sp…
Panopticon: Advancing Any-Sensor Foundation Models for Earth Observation
Leonard Waldmann, Ando Shah, Yi Wang +6
Earth observation (EO) data features diverse sensing platforms with varying spectral bands, spatial resolutions, and sensing modalities. While most prior work has constrained input…