20 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…
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:…
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…
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…