665 citations · 1.6k across the 58 of their papers we have counts for
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Oriented Tiny Object Detection: A Dataset, Benchmark, and Dynamic Unbiased Learning
Chang Xu, Ruixiang Zhang, Wen Yang +4
Detecting oriented tiny objects, which are limited in appearance information yet prevalent in real-world applications, remains an intricate and under-explored problem. To address t…
Tiny Object Detection with Single Point Supervision
Haoran Zhu, Chang Xu, Ruixiang Zhang +4
Tiny objects, with their limited spatial resolution, often resemble point-like distributions. As a result, bounding box prediction using point-level supervision emerges as a natura…
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…
Frequency-Adaptive Low-Latency Object Detection Using Events and Frames
Haitian Zhang, Xiangyuan Wang, Chang Xu +5
Fusing Events and RGB images for object detection leverages the robustness of Event cameras in adverse environments and the rich semantic information provided by RGB cameras. Howev…
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…
Unsupervised Multi-view UAV Image Geo-localization via Iterative Rendering
Haoyuan Li, Chang Xu, Wen Yang +3
Unmanned Aerial Vehicle (UAV) Cross-View Geo-Localization (CVGL) presents significant challenges due to the view discrepancy between oblique UAV images and overhead satellite image…
LaVIDE: Language-Prompted Satellite Change Detection via Map-Image Alignment
Shuguo Jiang, Fang Xu, Chuandong Liu +6
Remote sensing change detection based on a map reference and an up-to-date image boosts timely observation of the Earth's surface when earlier images are lacking for comparison. Ho…
Enhancing Fine-grained Object Detection in Aerial Images via Orthogonal Mapping
Haoran Zhu, Yifan Zhou, Chang Xu +2
Fine-Grained Object Detection (FGOD) is a critical task in high-resolution aerial image analysis. This letter introduces Orthogonal Mapping (OM), a simple yet effective method aime…
Detecting Every Object from Events
Haitian Zhang, Chang Xu, Xinya Wang +4
Object detection is critical in autonomous driving, and it is more practical yet challenging to localize objects of unknown categories: an endeavour known as Class-Agnostic Object…
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-…
FE-DeTr: Keypoint Detection and Tracking in Low-quality Image Frames with Events
Xiangyuan Wang, Kuangyi Chen, Wen Yang +3
Keypoint detection and tracking in traditional image frames are often compromised by image quality issues such as motion blur and extreme lighting conditions. Event cameras offer p…
ConGeo: Robust Cross-view Geo-localization across Ground View Variations
Li Mi, Chang Xu, Javiera Castillo-Navarro +4
Cross-view geo-localization aims at localizing a ground-level query image by matching it to its corresponding geo-referenced aerial view. In real-world scenarios, the task requires…
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…