no code implementations • 2 Feb 2024 • Zhuo Zheng, Yanfei Zhong, Liangpei Zhang, Stefano Ermon
Visual foundation models have achieved remarkable results in zero-shot image classification and segmentation, but zero-shot change detection remains an open problem.
no code implementations • 21 Jan 2024 • Yinhe Liu, Sunan Shi, Zhuo Zheng, Jue Wang, Shiqi Tian, Yanfei Zhong
Semantic Change Detection (SCD) is recognized as both a crucial and challenging task in the field of image analysis.
1 code implementation • 19 Dec 2023 • Junjue Wang, Zhuo Zheng, Zihang Chen, Ailong Ma, Yanfei Zhong
Earth vision research typically focuses on extracting geospatial object locations and categories but neglects the exploration of relations between objects and comprehensive reasoning.
Ranked #1 on Visual Question Answering on EarthVQA
1 code implementation • 11 Oct 2023 • Jingtao Li, Xinyu Wang, Hengwei Zhao, Liangpei Zhang, Yanfei Zhong
Firstly, we reformulate the anomaly detection task as an undirected bilayer graph based on the deviation relationship, where the anomaly score is modeled as the conditional probability, given the pattern of the background and normal objects.
1 code implementation • ICCV 2023 • Zhuo Zheng, Shiqi Tian, Ailong Ma, Liangpei Zhang, Yanfei Zhong
To solve these two problems, we present the change generator (Changen), a GAN-based GPCM, enabling controllable object change data generation, including customizable object property, and change event.
Ranked #1 on Change Detection on S2Looking
no code implementations • ICCV 2023 • Yinhe Liu, Sunan Shi, Junjue Wang, Yanfei Zhong
This shortcoming poses a significant challenge in processing complex and variable geo-objects, which results in semantic inconsistency in segmentation results.
1 code implementation • ICCV 2023 • Hengwei Zhao, Xinyu Wang, Jingtao Li, Yanfei Zhong
Positive-unlabeled learning (PU learning) in hyperspectral remote sensing imagery (HSI) is aimed at learning a binary classifier from positive and unlabeled data, which has broad prospects in various earth vision applications.
no code implementations • IEEE Transactions on Pattern Analysis and Machine Intelligence 2023 • Zhuo Zheng, Yanfei Zhong, Junjue Wang, Ailong Ma, Liangpei Zhang
Generic semantic segmentation methods mainly focus on the scale variation in natural scenarios.
1 code implementation • 22 Mar 2023 • Jingtao Li, Xinyu Wang, Shaoyu Wang, Hengwei Zhao, Liangpei Zhang, Yanfei Zhong
In this paper, an unsupervised transferred direct detection (TDD) model is proposed, which is optimized directly for the anomaly detection task (one-step paradigm) and has transferability.
1 code implementation • 31 Jan 2023 • Jingtao Li, Xinyu Wang, Hengwei Zhao, Shaoyu Wang, Yanfei Zhong
Anomaly segmentation in high spatial resolution (HSR) remote sensing imagery is aimed at segmenting anomaly patterns of the earth deviating from normal patterns, which plays an important role in various Earth vision applications.
no code implementations • 27 Oct 2022 • Hengwei Zhao, Yanfei Zhong, Xinyu Wang, Hong Shu
Hyperspectral imagery (HSI) one-class classification is aimed at identifying a single target class from the HSI by using only knowing positive data, which can significantly reduce the requirements for annotation.
no code implementations • 6 Sep 2022 • Omid Ghorbanzadeh, Yonghao Xu, Hengwei Zhao, Junjue Wang, Yanfei Zhong, Dong Zhao, Qi Zang, Shuang Wang, Fahong Zhang, Yilei Shi, Xiao Xiang Zhu, Lin Bai, Weile Li, Weihang Peng, Pedram Ghamisi
The objective of the competition is to automatically detect landslides based on large-scale multiple sources of satellite imagery collected globally.
1 code implementation • 11 May 2022 • Chenyu Zheng, Junjue Wang, Ailong Ma, Yanfei Zhong
Land-cover classification has long been a hot and difficult challenge in remote sensing community.
4 code implementations • 17 Oct 2021 • Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, Yanfei Zhong
Deep learning approaches have shown promising results in remote sensing high spatial resolution (HSR) land-cover mapping.
Ranked #12 on Semantic Segmentation on LoveDA
2 code implementations • ICCV 2021 • Zhuo Zheng, Ailong Ma, Liangpei Zhang, Yanfei Zhong
For high spatial resolution (HSR) remote sensing images, bitemporal supervised learning always dominates change detection using many pairwise labeled bitemporal images.
Ranked #13 on Change Detection on LEVIR-CD
Building change detection for remote sensing images Change detection for remote sensing images +1
1 code implementation • IEEE Transactions on Geoscience and Remote Sensing 2021 • Ailong Ma, Junjue Wang, Yanfei Zhong, Zhuo Zheng
The small object semantic segmentation task is aimed at automatically extracting key objects from high-resolution remote sensing (HRS) imagery.
Ranked #13 on Semantic Segmentation on iSAID
1 code implementation • 29 May 2021 • Qiqi Zhu, Weihuan Deng, Zhuo Zheng, Yanfei Zhong, Qingfeng Guan, Weihua Lin, Liangpei Zhang, Deren Li
However, FPGA has difficulty extracting the most discriminative features when the sample data is imbalanced.
Ranked #1 on Hyperspectral Image Classification on Indian Pines (Kappa metric, using extra training data)
no code implementations • 27 Dec 2020 • Xin Hu, Yanfei Zhong, Chang Luo, Xinyu Wang
Some start-of-art hyperspectral image classification methods benchmarked the WHU-Hi dataset, and the experimental results show that WHU-Hi is a challenging dataset.
2 code implementations • CVPR 2020 • Zhuo Zheng, Yanfei Zhong, Junjue Wang, Ailong Ma
However, general semantic segmentation methods mainly focus on scale variation in the natural scene, with inadequate consideration of the other two problems that usually happen in the large area earth observation scene.
Ranked #18 on Semantic Segmentation on iSAID
1 code implementation • 11 Nov 2020 • Zhuo Zheng, Yanfei Zhong, Ailong Ma, Liangpei Zhang
In this paper, a fast patch-free global learning (FPGA) framework is proposed for HSI classification.
Ranked #1 on Hyperspectral Image Classification on Pavia University (OA@200 metric)
2 code implementations • 6 Nov 2020 • Shiqi Tian, Ailong Ma, Zhuo Zheng, Yanfei Zhong
With the acceleration of the urban expansion, urban change detection (UCD), as a significant and effective approach, can provide the change information with respect to geospatial objects for dynamical urban analysis.
no code implementations • 23 Jul 2017 • Xin-Yi Tong, Gui-Song Xia, Fan Hu, Yanfei Zhong, Mihai Datcu, Liangpei Zhang
Over the past two decades, a large amount of research on this task has been carried out, which mainly focuses on the following three core issues: feature extraction, similarity metric and relevance feedback.
1 code implementation • 18 Aug 2016 • Gui-Song Xia, Jingwen Hu, Fan Hu, Baoguang Shi, Xiang Bai, Yanfei Zhong, Liangpei Zhang
The goal of AID is to advance the state-of-the-arts in scene classification of remote sensing images.