40 citations · 87 across the 13 of their papers we have counts for
13 papers
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…
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…
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…
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…
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…
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…
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…
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…
Spectrum-driven Mixed-frequency Network for Hyperspectral Salient Object Detection
Peifu Liu, Tingfa Xu, Huan Chen +3
Hyperspectral salient object detection (HSOD) aims to detect spectrally salient objects in hyperspectral images (HSIs). However, existing methods inadequately utilize spectral info…
Spectral-wise Implicit Neural Representation for Hyperspectral Image Reconstruction
Huan Chen, Wangcai Zhao, Tingfa Xu +3
Coded Aperture Snapshot Spectral Imaging (CASSI) reconstruction aims to recover the 3D spatial-spectral signal from 2D measurement. Existing methods for reconstructing Hyperspectra…