562 citations · 1.8k across the 22 of their papers we have counts for
22 papers
OGMN: Occlusion-guided Multi-task Network for Object Detection in UAV Images
Xuexue Li, Wenhui Diao, Yongqiang Mao +4
Occlusion between objects is one of the overlooked challenges for object detection in UAV images. Due to the variable altitude and angle of UAVs, occlusion in UAV images happens mo…
LIGHT: Joint Individual Building Extraction and Height Estimation from Satellite Images through a Unified Multitask Learning Network
Yongqiang Mao, Xian Sun, Xingliang Huang +1
Building extraction and height estimation are two important basic tasks in remote sensing image interpretation, which are widely used in urban planning, real-world 3D construction,…
SiamTHN: Siamese Target Highlight Network for Visual Tracking
Jiahao Bao, Kaiqiang Chen, Xian Sun +3
Siamese network based trackers develop rapidly in the field of visual object tracking in recent years. The majority of siamese network based trackers now in use treat each channel…
Elevation Estimation-Driven Building 3D Reconstruction from Single-View Remote Sensing Imagery
Yongqiang Mao, Kaiqiang Chen, Liangjin Zhao +7
Building 3D reconstruction from remote sensing images has a wide range of applications in smart cities, photogrammetry and other fields. Methods for automatic 3D urban building mod…
Breaking Immutable: Information-Coupled Prototype Elaboration for Few-Shot Object Detection
Xiaonan Lu, Wenhui Diao, Yongqiang Mao +4
Few-shot object detection, expecting detectors to detect novel classes with a few instances, has made conspicuous progress. However, the prototypes extracted by existing meta-learn…
Probabilistic Deep Metric Learning for Hyperspectral Image Classification
Chengkun Wang, Wenzhao Zheng, Xian Sun +2
This paper proposes a probabilistic deep metric learning (PDML) framework for hyperspectral image classification, which aims to predict the category of each pixel for an image capt…
Learning to Evaluate Performance of Multi-modal Semantic Localization
Zhiqiang Yuan, Wenkai Zhang, Chongyang Li +6
Semantic localization (SeLo) refers to the task of obtaining the most relevant locations in large-scale remote sensing (RS) images using semantic information such as text. As an em…
Beyond single receptive field: A receptive field fusion-and-stratification network for airborne laser scanning point cloud classification
Yongqiang Mao, Kaiqiang Chen, Wenhui Diao +4
The classification of airborne laser scanning (ALS) point clouds is a critical task of remote sensing and photogrammetry fields. Although recent deep learning-based methods have ac…
Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval
Zhiqiang Yuan, Wenkai Zhang, Kun Fu +4
Remote sensing (RS) cross-modal text-image retrieval has attracted extensive attention for its advantages of flexible input and efficient query. However, traditional methods ignore…
Double Similarity Distillation for Semantic Image Segmentation
Yingchao Feng, Xian Sun, Wenhui Diao +2
The balance between high accuracy and high speed has always been a challenging task in semantic image segmentation. Compact segmentation networks are more widely used in the case o…
HYPER^2: Hyperbolic Poincare Embedding for Hyper-Relational Link Prediction
Shiyao Yan, Zequn Zhang, Xian Sun +3
Link Prediction, addressing the issue of completing KGs with missing facts, has been broadly studied. However, less light is shed on the ubiquitous hyper-relational KGs. Most exist…
FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagery
Xian Sun, Peijin Wang, Zhiyuan Yan +11
With the rapid development of deep learning, many deep learning-based approaches have made great achievements in object detection task. It is generally known that deep learning is…
High Quality Remote Sensing Image Super-Resolution Using Deep Memory Connected Network
Wenjia Xu, Guangluan Xu, Yang Wang +3
Single image super-resolution is an effective way to enhance the spatial resolution of remote sensing image, which is crucial for many applications such as target detection and ima…
Ship Instance Segmentation From Remote Sensing Images Using Sequence Local Context Module
Yingchao Feng, Wenhui Diao, Zhonghan Chang +3
The performance of object instance segmentation in remote sensing images has been greatly improved through the introduction of many landmark frameworks based on convolutional neura…
A Training-free, One-shot Detection Framework For Geospatial Objects In Remote Sensing Images
Tengfei Zhang, Yue Zhang, Xian Sun +3
Deep learning based object detection has achieved great success. However, these supervised learning methods are data-hungry and time-consuming. This restriction makes them unsuitab…
Comparison Network for One-Shot Conditional Object Detection
Tengfei Zhang, Yue Zhang, Xian Sun +4
The current advances in object detection depend on large-scale datasets to get good performance. However, there may not always be sufficient samples in many scenarios, which leads…
A Remote Sensing Image Dataset for Cloud Removal
Daoyu Lin, Guangluan Xu, Xiaoke Wang +3
Cloud-based overlays are often present in optical remote sensing images, thus limiting the application of acquired data. Removing clouds is an indispensable pre-processing step in…
Wider Channel Attention Network for Remote Sensing Image Super-resolution
Jun Gu, Guangluan Xu, Yue Zhang +3
Recently, deep convolutional neural networks (CNNs) have obtained promising results in image processing tasks including super-resolution (SR). However, most CNN-based SR methods tr…
SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated Objects
Xue Yang, Jirui Yang, Junchi Yan +5
Object detection has been a building block in computer vision. Though considerable progress has been made, there still exist challenges for objects with small size, arbitrary direc…
Automatic Ship Detection of Remote Sensing Images from Google Earth in Complex Scenes Based on Multi-Scale Rotation Dense Feature Pyramid Networks
Xue Yang, Hao Sun, Kun Fu +4
Ship detection has been playing a significant role in the field of remote sensing for a long time but it is still full of challenges. The main limitations of traditional ship detec…
Position Detection and Direction Prediction for Arbitrary-Oriented Ships via Multitask Rotation Region Convolutional Neural Network
Xue Yang, Hao Sun, Xian Sun +3
Ship detection is of great importance and full of challenges in the field of remote sensing. The complexity of application scenarios, the redundancy of detection region, and the di…
MARTA GANs: Unsupervised Representation Learning for Remote Sensing Image Classification
Daoyu Lin, Kun Fu, Yang Wang +2
With the development of deep learning, supervised learning has frequently been adopted to classify remotely sensed images using convolutional networks (CNNs). However, due to the l…