240 citations · 771 across the 12 of their papers we have counts for
13 papers
Towards UAV Detection in the Real World: A New Multispectral Dataset UAVNet-MS and a New Method
Yihang Luo, Jun Chen, Chao Xiao +13
The proliferation of unmanned aerial vehicles (UAVs) has created urgent demand for precise UAV monitoring. Existing RGB-based systems rely on spatial cues that degrade at small sca…
Dynamic High-frequency Convolution for Infrared Small Target Detection
Ruojing Li, Chao Xiao, Qian Yin +5
Infrared small targets are typically tiny and locally salient, which belong to high-frequency components (HFCs) in images. Single-frame infrared small target (SIRST) detection is c…
Event-based Tiny Object Detection: A Benchmark Dataset and Baseline
Nuo Chen, Chao Xiao, Yimian Dai +3
Small object detection (SOD) in anti-UAV task is a challenging problem due to the small size of UAVs and complex backgrounds. Traditional frame-based cameras struggle to detect sma…
Heterogeneous Graph Transformer for Multiple Tiny Object Tracking in RGB-T Videos
Qingyu Xu, Longguang Wang, Weidong Sheng +4
Tracking multiple tiny objects is highly challenging due to their weak appearance and limited features. Existing multi-object tracking algorithms generally focus on single-modality…
Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos
C. Xiao, W. An, Y. Zhang +5
Moving object detection in satellite videos (SVMOD) is a challenging task due to the extremely dim and small target characteristics. Current learning-based methods extract spatio-t…
Visible-Thermal Tiny Object Detection: A Benchmark Dataset and Baselines
Xinyi Ying, Chao Xiao, Ruojing Li +13
Small object detection (SOD) has been a longstanding yet challenging task for decades, with numerous datasets and algorithms being developed. However, they mainly focus on either v…
DiffDet4SAR: Diffusion-based Aircraft Target Detection Network for SAR Images
Zhou Jie, Xiao Chao, Peng Bo +4
Aircraft target detection in SAR images is a challenging task due to the discrete scattering points and severe background clutter interference. Currently, methods with convolution-…
You Only Train Once: Learning a General Anomaly Enhancement Network with Random Masks for Hyperspectral Anomaly Detection
Zhaoxu Li, Yingqian Wang, Chao Xiao +3
In this paper, we introduce a new approach to address the challenge of generalization in hyperspectral anomaly detection (AD). Our method eliminates the need for adjusting paramete…
MTU-Net: Multi-level TransUNet for Space-based Infrared Tiny Ship Detection
Tianhao Wu, Boyang Li, Yihang Luo +6
Space-based infrared tiny ship detection aims at separating tiny ships from the images captured by earth orbiting satellites. Due to the extremely large image coverage area (e.g.,…
Dense Dual-Attention Network for Light Field Image Super-Resolution
Yu Mo, Yingqian Wang, Chao Xiao +2
Light field (LF) images can be used to improve the performance of image super-resolution (SR) because both angular and spatial information is available. It is challenging to incorp…
Selective Light Field Refocusing for Camera Arrays Using Bokeh Rendering and Superresolution
Yingqian Wang, Jungang Yang, Yulan Guo +2
Camera arrays provide spatial and angular information within a single snapshot. With refocusing methods, focal planes can be altered after exposure. In this letter, we propose a li…
Dense Nested Attention Network for Infrared Small Target Detection
Boyang Li, Chao Xiao, Longguang Wang +5
Single-frame infrared small target (SIRST) detection aims at separating small targets from clutter backgrounds. With the advances of deep learning, CNN-based methods have yielded p…
Non-Convex Tensor Low-Rank Approximation for Infrared Small Target Detection
Ting Liu, Jungang Yang, Boyang Li +4
Infrared small target detection is an important fundamental task in the infrared system. Therefore, many infrared small target detection methods have been proposed, in which the lo…