Search Results for author: Yanfei Zhong

Found 23 papers, 15 papers with code

Segment Any Change

no code implementations2 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.

Change Detection Image Classification +1

EarthVQA: Towards Queryable Earth via Relational Reasoning-Based Remote Sensing Visual Question Answering

1 code implementation19 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.

Object Object Counting +3

A Unified Remote Sensing Anomaly Detector Across Modalities and Scenes via Deviation Relationship Learning

1 code implementation11 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.

Anomaly Detection Earth Observation

Scalable Multi-Temporal Remote Sensing Change Data Generation via Simulating Stochastic Change Process

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.

Change Data Generation Change Detection

Class Prior-Free Positive-Unlabeled Learning with Taylor Variational Loss for Hyperspectral Remote Sensing Imagery

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.

One-Step Detection Paradigm for Hyperspectral Anomaly Detection via Spectral Deviation Relationship Learning

1 code implementation22 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.

Anomaly Detection

Anomaly Segmentation for High-Resolution Remote Sensing Images Based on Pixel Descriptors

1 code implementation31 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.

One-Class Classification Segmentation

One-Class Risk Estimation for One-Class Hyperspectral Image Classification

no code implementations27 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.

Classification Hyperspectral Image Classification +3

LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation

4 code implementations17 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.

Pseudo Label Segmentation +2

WHU-Hi: UAV-borne hyperspectral with high spatial resolution (H2) benchmark datasets for hyperspectral image classification

no code implementations27 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.

Classification General Classification +1

Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagery

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.

Earth Observation Relation +4

Hi-UCD: A Large-scale Dataset for Urban Semantic Change Detection in Remote Sensing Imagery

2 code implementations6 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.

Change Detection

Exploiting Deep Features for Remote Sensing Image Retrieval: A Systematic Investigation

no code implementations23 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.

Image Retrieval Retrieval

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