233 citations · 693 across the 45 of their papers we have counts for
47 papers
Spectral-Aware Proposal Enhancement for Diffusion-Based Multispectral UAV Multi-Object Tracking
Xu Lin, Tingfa Xu, Tianhao Li +4
Multispectral UAV multi-object tracking (MOT) with oriented bounding boxes remains challenging due to small targets, cluttered backgrounds, and unstable inter-frame associations. A…
Spectral-Spatial Synergistic Guided Network for Hyperspectral Salient Object Detection
Yanyan Peng, Tingfa Xu, Yao Xiao +4
Hyperspectral salient object detection aims to identify visually salient regions from hyperspectral images. Existing methods often fail because they fundamentally misunderstand the…
Fully Rotation-Equivariant Spectral-Spatial Learning for Multispectral Object Detection
Peng Zhang, Tingfa Xu, Shuaihao Han +1
Existing multispectral detectors are limited by discrete spectral processing, a scale-dependent shift in the relative reliability of spectral and spatial cues across pyramid levels…
Hyperspectral Image Classification via Efficient Global Spectral Supertoken Clustering
Peifu Liu, Tingfa Xu, Jie Wang +3
Hyperspectral image classification demands spatially coherent predictions and precise boundary delineation. Yet prevailing superpixel-based methods face an inherent contradiction:…
HyperCOD: The First Challenging Benchmark and Baseline for Hyperspectral Camouflaged Object Detection
Shuyan Bai, Tingfa Xu, Peifu Liu +5
RGB-based camouflaged object detection struggles in real-world scenarios where color and texture cues are ambiguous. While hyperspectral image offers a powerful alternative by capt…
Efficient Hyperspectral Image Reconstruction Using Lightweight Separate Spectral Transformers
Jianan Li, Wangcai Zhao, Tingfa Xu
Hyperspectral imaging (HSI) is essential across various disciplines for its capacity to capture rich spectral information. However, efficiently reconstructing hyperspectral images…
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…
Spectrum-oriented Point-supervised Saliency Detector for Hyperspectral Images
Peifu Liu, Tingfa Xu, Guokai Shi +3
Hyperspectral salient object detection (HSOD) aims to extract targets or regions with significantly different spectra from hyperspectral images. While existing deep learning-based…
Target-Guided Adversarial Point Cloud Transformer Towards Recognition Against Real-world Corruptions
Jie Wang, Tingfa Xu, Lihe Ding +1
Achieving robust 3D perception in the face of corrupted data presents an challenging hurdle within 3D vision research. Contemporary transformer-based point cloud recognition models…
Content-driven Magnitude-Derivative Spectrum Complementary Learning for Hyperspectral Image Classification
Huiyan Bai, Tingfa Xu, Huan Chen +2
Extracting discriminative information from complex spectral details in hyperspectral image (HSI) for HSI classification is pivotal. While current prevailing methods rely on spectra…
Dual-stage Hyperspectral Image Classification Model with Spectral Supertoken
Peifu Liu, Tingfa Xu, Jie Wang +3
Hyperspectral image classification, a task that assigns pre-defined classes to each pixel in a hyperspectral image of remote sensing scenes, often faces challenges due to the negle…
DMSSN: Distilled Mixed Spectral-Spatial Network for Hyperspectral Salient Object Detection
Haolin Qin, Tingfa Xu, Peifu Liu +2
Hyperspectral salient object detection (HSOD) has exhibited remarkable promise across various applications, particularly in intricate scenarios where conventional RGB-based approac…
Multi-step Temporal Modeling for UAV Tracking
Xiaoying Yuan, Tingfa Xu, Xincong Liu +4
In the realm of unmanned aerial vehicle (UAV) tracking, Siamese-based approaches have gained traction due to their optimal balance between efficiency and precision. However, UAV sc…