233 citations · 693 across the 45 of their papers we have counts for
12 papers · 1 filter
MODA: The First Challenging Benchmark for Multispectral Object Detection in Aerial Images
Shuaihao Han, Tingfa Xu, Peifu Liu +1
Aerial object detection faces significant challenges in real-world scenarios, such as small objects and extensive background interference, which limit the performance of RGB-based…
MMOT: The First Challenging Benchmark for Drone-based Multispectral Multi-Object Tracking
Tianhao Li, Tingfa Xu, Ying Wang +3
Drone-based multi-object tracking is essential yet highly challenging due to small targets, severe occlusions, and cluttered backgrounds. Existing RGB-based tracking algorithms hea…
MSITrack: A Challenging Benchmark for Multispectral Single Object Tracking
Tao Feng, Tingfa Xu, Haolin Qin +5
Visual object tracking in real-world scenarios presents numerous challenges including occlusion, interference from similar objects and complex backgrounds-all of which limit the ef…
MCOD: The First Challenging Benchmark for Multispectral Camouflaged Object Detection
Yang Li, Tingfa Xu, Shuyan Bai +2
Camouflaged Object Detection (COD) aims to identify objects that blend seamlessly into natural scenes. Although RGB-based methods have advanced, their performance remains limited u…
COXNet: Cross-Layer Fusion with Adaptive Alignment and Scale Integration for RGBT Tiny Object Detection
Peiran Peng, Tingfa Xu, Liqiang Song +3
Detecting tiny objects in multimodal Red-Green-Blue-Thermal (RGBT) imagery is a critical challenge in computer vision, particularly in surveillance, search and rescue, and autonomo…
FBRT-YOLO: Faster and Better for Real-Time Aerial Image Detection
Yao Xiao, Tingfa Xu, Yu Xin +1
Embedded flight devices with visual capabilities have become essential for a wide range of applications. In aerial image detection, while many existing methods have partially addre…
FocusTrack: A Self-Adaptive Local Sampling Algorithm for Efficient Anti-UAV Tracking
Ying Wang, Tingfa Xu, Jianan Li
Anti-UAV tracking poses significant challenges, including small target sizes, abrupt camera motion, and cluttered infrared backgrounds. Existing tracking paradigms can be broadly c…
PvNeXt: Rethinking Network Design and Temporal Motion for Point Cloud Video Recognition
Jie Wang, Tingfa Xu, Lihe Ding +3
Point cloud video perception has become an essential task for the realm of 3D vision. Current 4D representation learning techniques typically engage in iterative processing coupled…
Hyperspectral Remote Sensing Images Salient Object Detection: The First Benchmark Dataset and Baseline
Peifu Liu, Huiyan Bai, Tingfa Xu +3
The objective of hyperspectral remote sensing image salient object detection (HRSI-SOD) is to identify objects or regions that exhibit distinct spectrum contrasts with the backgrou…
MUST: The First Dataset and Unified Framework for Multispectral UAV Single Object Tracking
Haolin Qin, Tingfa Xu, Tianhao Li +3
UAV tracking faces significant challenges in real-world scenarios, such as small-size targets and occlusions, which limit the performance of RGB-based trackers. Multispectral image…
HSOD-BIT-V2: A New Challenging Benchmarkfor Hyperspectral Salient Object Detection
Yuhao Qiu, Shuyan Bai, Tingfa Xu +3
Salient Object Detection (SOD) is crucial in computer vision, yet RGB-based methods face limitations in challenging scenes, such as small objects and similar color features. Hypers…
Mixed-granularity Implicit Representation for Continuous Hyperspectral Compressive Reconstruction
Jianan Li, Huan Chen, Wangcai Zhao +2
Hyperspectral Images (HSIs) are crucial across numerous fields but are hindered by the long acquisition times associated with traditional spectrometers. The Coded Aperture Snapshot…