19 citations · 24 across the 5 of their papers we have counts for
5 papers
Changen2: Multi-Temporal Remote Sensing Generative Change Foundation Model
Zhuo Zheng, Stefano Ermon, Dongjun Kim +2
Our understanding of the temporal dynamics of the Earth's surface has been advanced by deep vision models, which often require lots of labeled multi-temporal images for training. H…
Single-Temporal Supervised Learning for Universal Remote Sensing Change Detection
Zhuo Zheng, Yanfei Zhong, Ailong Ma +1
Bitemporal supervised learning paradigm always dominates remote sensing change detection using numerous labeled bitemporal image pairs, especially for high spatial resolution (HSR)…
MapChange: Enhancing Semantic Change Detection with Temporal-Invariant Historical Maps Based on Deep Triplet Network
Yinhe Liu, Sunan Shi, Zhuo Zheng +3
Semantic Change Detection (SCD) is recognized as both a crucial and challenging task in the field of image analysis. Traditional methods for SCD have predominantly relied on the co…
Scalable Multi-Temporal Remote Sensing Change Data Generation via Simulating Stochastic Change Process
Zhuo Zheng, Shiqi Tian, Ailong Ma +2
Understanding the temporal dynamics of Earth's surface is a mission of multi-temporal remote sensing image analysis, significantly promoted by deep vision models with its fuel -- l…
Seeing Beyond the Patch: Scale-Adaptive Semantic Segmentation of High-resolution Remote Sensing Imagery based on Reinforcement Learning
Yinhe Liu, Sunan Shi, Junjue Wang +1
In remote sensing imagery analysis, patch-based methods have limitations in capturing information beyond the sliding window. This shortcoming poses a significant challenge in proce…