I am a Ph.D. student (2018-2023, expected) at State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University. I received B.S. degree from the School of Geography and Information Engineering, China University of Geosciences, Wuhan, China, in 2018. I'm now a member of RSIDEA group, advised by Prof. Yanfei Zhong and Prof. Liangpei Zhang.
My research interest is in remote sensing visual perception and earth vision, especially multi-modal and multi-temporal remote sensing image analysis. My research goal is to design original and insightful Earth vision technologies to make high positive impacts on the geoscience field. Meanwhile, I am an enthusiast of remote sensing data science competitions.
Update: I am looking for a postdoc research position to study Artificial Intelligence for Remote Sensing. Feel free to contact me.Email: zhengzhuo [at] whu [dot] edu [dot] cn
2021.12, Awarded with "Wang Zhizhuo Innovation Talent" Outstanding Prize.
2021.10, One paper is accepted by NeurIPS 2021 Datasets and Benchmarks.
2021.10, One paper is accepted by ISPRS P&RS.
2021.08, One paper is accepted by RSE.
2021.07, One paper is accepted by ICCV 2021.
2021.07, I win the 5th place in the Overhead Geopose Challenge hosted by NGA.
2021.03, Our team win the 4th place in 2021 IEEE GRSS Data Fusion Contest, Track: Multitemporal Semantic Change Detection.
2021.03, Our PE&RS paper wins the first place in the 2021 John I. Davidson President’s Award.
2020.12, One paper is accepted by ISPRS P&RS.
2020.11, the source code of FarSeg (CVPR 2020) has been available.
2020.10, Awarded with the 2020 Graduate Academic Innovation Outstanding Prize.
2020.06, I win the top graduate award at SpaceNet 6 & EarthVision workshop challenge at CVPR 2020.
2020.05, the source code of FPGA (TGRS 2020) has been available.
ChangeMask: Deep Multi-task Encoder-Transformer-Decoder Architecture for Semantic Change Detection
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Building Damage Assessment for Rapid Disaster Response with a Deep Object-based Semantic Change Detection Framework: from
natural disasters to man-made disasters
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Change is Everywhere: Single-Temporal Supervised Object Change Detection in
Remote Sensing Imagery
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LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation
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Deep Multisensor Learning for Missing-Modality All-Weather Mapping
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Foreground-Aware Relation Network for Geospatial Object Segmentation in High
Spatial Resolution Remote Sensing Imagery
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FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End
Hyperspectral Image Classification
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HyNet: Hyper-scale object detection network framework for multiple spatial
resolution remote sensing imagery
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COLOR: Cycling, Offline Learning, and Online Representation Framework for
Airport and Airplane Detection Using GF-2 Satellite Images
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