3.2k citations · 9.7k across the 58 of their papers we have counts for
37 papers · 1 filter
Self-Ensembling GAN for Cross-Domain Semantic Segmentation
Yonghao Xu, Fengxiang He, Bo Du +2
Deep neural networks (DNNs) have greatly contributed to the performance gains in semantic segmentation. Nevertheless, training DNNs generally requires large amounts of pixel-level…
LUAI Challenge 2021 on Learning to Understand Aerial Images
Gui-Song Xia, Jian Ding, Ming Qian +33
This report summarizes the results of Learning to Understand Aerial Images (LUAI) 2021 challenge held on ICCV 2021, which focuses on object detection and semantic segmentation in a…
Change is Everywhere: Single-Temporal Supervised Object Change Detection in Remote Sensing Imagery
Zhuo Zheng, Ailong Ma, Liangpei Zhang +1
For high spatial resolution (HSR) remote sensing images, bitemporal supervised learning always dominates change detection using many pairwise labeled bitemporal images. However, it…
A Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image Classification
Qiqi Zhu, Weihuan Deng, Zhuo Zheng +5
Deep learning techniques have been widely applied to hyperspectral image (HSI) classification and have achieved great success. However, the deep neural network model has a large pa…
Robust Self-Ensembling Network for Hyperspectral Image Classification
Yonghao Xu, Bo Du, Liangpei Zhang
Recent research has shown the great potential of deep learning algorithms in the hyperspectral image (HSI) classification task. Nevertheless, training these models usually requires…
Interpretable Hyperspectral AI: When Non-Convex Modeling meets Hyperspectral Remote Sensing
Danfeng Hong, Wei He, Naoto Yokoya +5
Hyperspectral imaging, also known as image spectrometry, is a landmark technique in geoscience and remote sensing (RS). In the past decade, enormous efforts have been made to proce…
Semantic Change Detection with Asymmetric Siamese Networks
Kunping Yang, Gui-Song Xia, Zicheng Liu +4
Given two multi-temporal aerial images, semantic change detection aims to locate the land-cover variations and identify their change types with pixel-wise boundaries. This problem…
An Investigation of Traffic Density Changes inside Wuhan during the COVID-19 Epidemic with GF-2 Time-Series Images
Chen Wu, Yinong Guo, Haonan Guo +5
In order to mitigate the spread of COVID-19, Wuhan was the first city to implement strict lockdown policy in 2020. Even though numerous researches have discussed the travel restric…
On Creating Benchmark Dataset for Aerial Image Interpretation: Reviews, Guidances and Million-AID
Yang Long, Gui-Song Xia, Shengyang Li +5
The past years have witnessed great progress on remote sensing (RS) image interpretation and its wide applications. With RS images becoming more accessible than ever before, there…
Holistically-Attracted Wireframe Parsing
Nan Xue, Tianfu Wu, Song Bai +4
This paper presents a fast and parsimonious parsing method to accurately and robustly detect a vectorized wireframe in an input image with a single forward pass. The proposed metho…
Learning Regional Attraction for Line Segment Detection
Nan Xue, Song Bai, Fu-Dong Wang +4
This paper presents regional attraction of line segment maps, and hereby poses the problem of line segment detection (LSD) as a problem of region coloring. Given a line segment map…
Learning Attraction Field Representation for Robust Line Segment Detection
Nan Xue, Song Bai, Fudong Wang +3
This paper presents a region-partition based attraction field dual representation for line segment maps, and thus poses the problem of line segment detection (LSD) as the region co…
Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-Temporal Remote Sensing Images
Bo Du, Lixiang Ru, Chen Wu +1
Change detection has been a hotspot in remote sensing technology for a long time. With the increasing availability of multi-temporal remote sensing images, numerous change detectio…
Hybrid Noise Removal in Hyperspectral Imagery With a Spatial-Spectral Gradient Network
Qiang Zhang, Qiangqiang Yuan, Jie Li +3
The existence of hybrid noise in hyperspectral images (HSIs) severely degrades the data quality, reduces the interpretation accuracy of HSIs, and restricts the subsequent HSIs appl…
Oblique Stripe Removal in Remote Sensing Images via Oriented Variation
Xinxin Liu, Xiliang Lu, Huanfeng Shen +2
Destriping is a classical problem in remote sensing image processing. Although considerable effort has been made to remove stripes, few of the existing methods can eliminate stripe…
Spatial-Spectral Fusion by Combining Deep Learning and Variation Model
Huanfeng Shen, Menghui Jiang, Jie Li +3
In the field of spatial-spectral fusion, the model-based method and the deep learning (DL)-based method are state-of-the-art. This paper presents a fusion method that incorporates…
Accurate Building Detection in VHR Remote Sensing Images using Geometric Saliency
Jin Huang, Gui-Song Xia, Fan Hu +1
This paper aims to address the problem of detecting buildings from remote sensing images with very high resolution (VHR). Inspired by the observation that buildings are always more…
Large-scale Land Cover Classification in GaoFen-2 Satellite Imagery
Xin-Yi Tong, Qikai Lu, Gui-Song Xia +1
Many significant applications need land cover information of remote sensing images that are acquired from different areas and times, such as change detection and disaster monitorin…
Recent advances and opportunities in scene classification of aerial images with deep models
Fan Hu, Gui-Song Xia, Wen Yang +1
Scene classification is a fundamental task in interpretation of remote sensing images, and has become an active research topic in remote sensing community due to its important role…
AID++: An Updated Version of AID on Scene Classification
Pu Jin, Gui-Song Xia, Fan Hu +2
Aerial image scene classification is a fundamental problem for understanding high-resolution remote sensing images and has become an active research task in the field of remote sen…
Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network
Qiangqiang Yuan, Qiang Zhang, Jie Li +2
Hyperspectral image (HSI) denoising is a crucial preprocessing procedure to improve the performance of the subsequent HSI interpretation and applications. In this paper, a novel de…
Learning the Synthesizability of Dynamic Texture Samples
Feng Yang, Gui-Song Xia, Dengxin Dai +1
A dynamic texture (DT) refers to a sequence of images that exhibit temporal regularities and has many applications in computer vision and graphics. Given an exemplar of dynamic tex…
A Multi-Scale and Multi-Depth Convolutional Neural Network for Remote Sensing Imagery Pan-Sharpening
Qiangqiang Yuan, Yancong Wei, Xiangchao Meng +2
Pan-sharpening is a fundamental and significant task in the field of remote sensing imagery processing, in which high-resolution spatial details from panchromatic images are employ…
DOTA: A Large-scale Dataset for Object Detection in Aerial Images
Gui-Song Xia, Xiang Bai, Jian Ding +6
Object detection is an important and challenging problem in computer vision. Although the past decade has witnessed major advances in object detection in natural scenes, such succe…