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20242026
most citedRethinking Scanning Strategies with Vision Mamba in Semantic Segmentation of Remote Sensing Imagery: An Experimental Study

64 citations · 72 across the 11 of their papers we have counts for

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cs.CV2026

Panoramic Scene Understanding: A Survey from Distortion-Aware Engineering to Sphere-Native Modeling

Qinfeng Zhu, Lei Fan

Panoramic images capture the full visual sphere in a frame, offering context unavailable to conventional cameras. Yet this completeness has an unavoidable geometric cost: the 2-sph…

cs.CV2026

A generalised pre-training strategy for deep learning networks in semantic segmentation of remotely sensed images

Yuan Fang, Yuanzhi Cai, Jagannath Aryal +4

In the segmentation of remotely sensed images, deep learning models are typically pre-trained using large image databases like ImageNet before fine-tuned on domain-specific dataset…

cs.CV2026

SO3UFormer: Learning Intrinsic Spherical Features for Rotation-Robust Panoramic Dense Prediction

Qinfeng Zhu, Yunxi Jiang, Lei Fan

Panoramic dense-prediction models, spanning semantic segmentation and depth estimation, are typically trained under a strict gravity-aligned assumption. Real-world captures, howeve…

cs.CV2025

SwinMamba: A hybrid local-global mamba framework for enhancing semantic segmentation of remotely sensed images

Qinfeng Zhu, Han Li, Liang He +1

Semantic segmentation of remote sensing imagery is a fundamental task in computer vision, supporting a wide range of applications such as land use classification, urban planning, a…

cs.CV2025★ 1 cited

ClassWise-CRF: Category-Specific Fusion for Enhanced Semantic Segmentation of Remote Sensing Imagery

Qinfeng Zhu, Yunxi Jiang, Lei Fan

We propose a result-level category-specific fusion architecture called ClassWise-CRF. This architecture employs a two-stage process: first, it selects expert networks that perform…

cs.CV2024★ 2 cited

MSCrackMamba: Leveraging Vision Mamba for Crack Detection in Fused Multispectral Imagery

Qinfeng Zhu, Yuan Fang, Lei Fan

Crack detection is a critical task in structural health monitoring, aimed at assessing the structural integrity of bridges, buildings, and roads to prevent potential failures. Visi…

cs.CV2024

Evaluating the Impact of Point Cloud Colorization on Semantic Segmentation Accuracy

Qinfeng Zhu, Jiaze Cao, Yuanzhi Cai +1

Point cloud semantic segmentation, the process of classifying each point into predefined categories, is essential for 3D scene understanding. While image-based segmentation is wide…

cs.CV2024

Enhancing Environmental Monitoring through Multispectral Imaging: The WasteMS Dataset for Semantic Segmentation of Lakeside Waste

Qinfeng Zhu, Ningxin Weng, Lei Fan +1

Environmental monitoring of lakeside green areas is crucial for environmental protection. Compared to manual inspections, computer vision technologies offer a more efficient soluti…

cs.CV2024★ 4 cited

Seg-LSTM: Performance of xLSTM for Semantic Segmentation of Remotely Sensed Images

Qinfeng Zhu, Yuanzhi Cai, Lei Fan

Recent advancements in autoregressive networks with linear complexity have driven significant research progress, demonstrating exceptional performance in large language models. A r…

cs.CV2024★ 64 cited

Rethinking Scanning Strategies with Vision Mamba in Semantic Segmentation of Remote Sensing Imagery: An Experimental Study

Qinfeng Zhu, Yuan Fang, Yuanzhi Cai +2

Deep learning methods, especially Convolutional Neural Networks (CNN) and Vision Transformer (ViT), are frequently employed to perform semantic segmentation of high-resolution remo…

cs.CV2024★ 1 cited

Samba: Semantic Segmentation of Remotely Sensed Images with State Space Model

Qinfeng Zhu, Yuanzhi Cai, Yuan Fang +4

High-resolution remotely sensed images pose a challenge for commonly used semantic segmentation methods such as Convolutional Neural Network (CNN) and Vision Transformer (ViT). CNN…