258 citations · 314 across the 14 of their papers we have counts for
14 papers
Hierarchical Fine-Grained Aerial Object Detection
Yan Zhang, Fang Xu, Wen Yang +1
Fine-grained aerial object detection, driven by the intrinsic granularity of real-world object categories, is crucial for advanced scene understanding in remote sensing. Existing m…
UHR-DETR: Efficient End-to-End Small Object Detection for Ultra-High-Resolution Remote Sensing Imagery
Jingfang Li, Haoran Zhu, Wen Yang +4
Ultra-High-Resolution (UHR) imagery has become essential for modern remote sensing, offering unprecedented spatial coverage. However, detecting small objects in such vast scenes pr…
Generalized Small Object Detection:A Point-Prompted Paradigm and Benchmark
Haoran Zhu, Wen Yang, Guangyou Yang +5
Small object detection (SOD) remains challenging due to extremely limited pixels and ambiguous object boundaries. These characteristics lead to challenging annotation, limited avai…
Unifying UAV Cross-View Geo-Localization via 3D Geometric Perception
Haoyuan Li, Wen Yang, Fang Xu +4
Cross-view geo-localization for Unmanned Aerial Vehicles (UAVs) operating in GNSS-denied environments remains challenging due to the severe geometric discrepancy between oblique UA…
Mask Clustering-based Annotation Engine for Large-Scale Submeter Land Cover Mapping
Hao Chen, Fang Xu, Tamer Saleh +2
Recent advances in remote sensing technology have made submeter resolution imagery increasingly accessible, offering remarkable detail for fine-grained land cover analysis. However…
QuadricsReg: Large-Scale Point Cloud Registration using Quadric Primitives
Ji Wu, Huai Yu, Shu Han +4
In the realm of large-scale point cloud registration, designing a compact symbolic representation is crucial for efficiently processing vast amounts of data, ensuring registration…
MCVO: A Generic Visual Odometry for Arbitrarily Arranged Multi-Cameras
Huai Yu, Junhao Wang, Yao He +2
Making multi-camera visual SLAM systems easier to set up and more robust to the environment is attractive for vision robots. Existing monocular and binocular vision SLAM systems ha…
Unleashing Unlabeled Data: A Paradigm for Cross-View Geo-Localization
Guopeng Li, Ming Qian, Gui-Song Xia
This paper investigates the effective utilization of unlabeled data for large-area cross-view geo-localization (CVGL), encompassing both unsupervised and semi-supervised settings.…
Learning Cross-view Visual Geo-localization without Ground Truth
Haoyuan Li, Chang Xu, Wen Yang +2
Cross-View Geo-Localization (CVGL) involves determining the geographical location of a query image by matching it with a corresponding GPS-tagged reference image. Current state-of-…
HiCD: Change Detection in Quality-Varied Images via Hierarchical Correlation Distillation
Chao Pang, Xingxing Weng, Jiang Wu +2
Advanced change detection techniques primarily target image pairs of equal and high quality. However, variations in imaging conditions and platforms frequently lead to image pairs…
Robust Tiny Object Detection in Aerial Images amidst Label Noise
Haoran Zhu, Chang Xu, Wen Yang +3
Precise detection of tiny objects in remote sensing imagery remains a significant challenge due to their limited visual information and frequent occurrence within scenes. This chal…
Rethinking Scale Imbalance in Semi-supervised Object Detection for Aerial Images
Ruixiang Zhang, Chang Xu, Fang Xu +4
This paper focuses on the scale imbalance problem of semi-supervised object detection(SSOD) in aerial images. Compared to natural images, objects in aerial images show smaller size…
Holistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning
Nan Xue, Tianfu Wu, Song Bai +4
This article presents Holistically-Attracted Wireframe Parsing (HAWP), a method for geometric analysis of 2D images containing wireframes formed by line segments and junctions. HAW…
X-ModalNet: A Semi-Supervised Deep Cross-Modal Network for Classification of Remote Sensing Data
Danfeng Hong, Naoto Yokoya, Gui-Song Xia +2
This paper addresses the problem of semi-supervised transfer learning with limited cross-modality data in remote sensing. A large amount of multi-modal earth observation images, su…