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zhuqinfeng1999/README.md
Qinfeng Zhu — spatial intelligence research across remote sensing, panoramic vision and 3D perception

Website ↗  ·   Research Atlas ↗  ·   Publications ↗  ·   Google Scholar ↗  ·   CV · July 2026 ↓

Hello — I’m Qinfeng.

I am a Ph.D. researcher at Xi’an Jiaotong-Liverpool University and the University of Liverpool, advised by Dr. Lei Fan. I received an MRes in Computer Science from the University of Liverpool in 2023.

My work studies how machines build reliable spatial understanding from satellite and aerial imagery, 360° panoramas, multispectral observations, and 3D point clouds. I am especially interested in representations that respect the geometry and sensing process of the world they model.

Current vector  ·  Seeking research internships in 2026  ·  Seeking full-time opportunities in academia or industry after graduating in 2027

Research coordinates

Research atlas connecting seven directions: remote sensing, 3D computer vision, panoramic vision, multimodal fusion, semantic segmentation, data augmentation and deep learning

EARTH OBSERVATION · SPHERE-NATIVE PERCEPTION · SPATIAL INTELLIGENCE · SENSOR FUSION · DENSE PREDICTION

Selected research

Visual overview of SemanticUrban, SO3UFormer and Panoramic Scene Understanding research

  1. Towards accurate urban scene understanding using point clouds: The SemanticUrban dataset
    Expert Systems with Applications, 2026 · Co-first author · Dataset · Code

  2. SO3UFormer: Learning Intrinsic Spherical Features for Rotation-Robust Panoramic Dense Prediction
    Under review, 2026 · Sphere-native panoramic modeling · Project · Code

  3. Panoramic Scene Understanding: A Survey from Distortion-Aware Engineering to Sphere-Native Modeling
    Under review, 2026 · A structured map of panoramic perception · Research map · Repository

  4. ClassWise-CRF: Category-Specific Fusion for Enhanced Semantic Segmentation of Remote Sensing Imagery
    Neural Networks, 2026 · Category-aware expert fusion · Code

  5. SwinMamba: A Hybrid Local-Global Mamba Framework for Enhancing Semantic Segmentation of Remotely Sensed Images
    Digital Signal Processing, 2026 · Local-global state-space modeling · DOI

Browse all 16 publications →

Open research artifacts

Artifact Research scope
SO3UFormer Sphere-native panoramic dense prediction
360° vision · geometry
Panoramic Scene Analysis Curated taxonomy and literature map
survey · research map
SemanticUrban High-resolution urban terrestrial point clouds
dataset · 3D perception
ClassWise-CRF Category-specific expert-network fusion
remote sensing · segmentation
IndoorMS Indoor multispectral semantic segmentation
dataset · multimodal
WasteMS Lakeside-waste multispectral benchmark
environment · multispectral
Samba · Seg-LSTM State-space and recurrent models for Earth observation
Mamba · xLSTM

Let’s connect

I welcome research collaborations, thoughtful conversations, and opportunities around spatial intelligence, Earth observation, panoramic perception, multimodal sensing, and 3D scene understanding.

Email  ·   LinkedIn  ·   ORCID  ·   ResearchGate

From pixels to points, from Earth to sphere

Pinned Loading

  1. ClassWise-CRF ClassWise-CRF Public

    Classwise-CRF: Category-specific fusion for enhanced semantic segmentation of remote sensing imagery

    Python 6

  2. SO3UFormer SO3UFormer Public

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

    Python 6

  3. YuanFangFF/SemanticUrban YuanFangFF/SemanticUrban Public

    This is the official repository for "Towards Accurate Urban Scene Understanding using Point Clouds: The SemanticUrban Dataset".

    17 1

  4. Awesome-Panoramic-Scene-Analysis Awesome-Panoramic-Scene-Analysis Public

    Official repository for "Panoramic Scene Analysis: A Survey from Distortion-Aware Engineering to Sphere-Native Foundation Modeling".

    15