works on

From the 1 of 7 linked papers with an AI index.

activity
20242026
collaborators

7 papers

cs.CV2026

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

Qinfeng Zhu, Lei Fan

The paper surveys methods for understanding panoramic images, covering techniques that handle projection distortions, sphere-native models, and adaptations of pretrained vision fou…

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.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.CV2025

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.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.CV2024

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…