Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

LangSurf: Language-Embedded Surface Gaussians for 3D Scene Understanding.

IEEE transactions on pattern analysis and machine intelligence·2026

Same author

Breathing New Life into Small Object Detection with Detection-Oriented Rectification.

IEEE transactions on pattern analysis and machine intelligence·2026

Same author

PathTIGR: A pathway topology-informed graph representation learning framework for immunotherapy response prediction.

Science advances·2026

Same author

Interpretable graph deep learning framework for drug synergy prediction by integrating functional and clinical similarities.

NPJ digital medicine·2026

Same author

Pre-Fluorinated SEI by Catalyzing a Parasitic Reaction Toward Stable Silicon Anodes.

Small (Weinheim an der Bergstrasse, Germany)·2026

Same author

Stress-Mediated Lattice Reconstruction Regenerates Spent LiFePO<sub>4</sub> Cathodes.

Advanced materials (Deerfield Beach, Fla.)·2026

Same journal

A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

TraGraph-GS: Trajectory Graph-based Gaussian Splatting for Arbitrary Large-Scale Scene Rendering.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

SWIFT: A Small-World Interaction Framework for Flow-Aware Trajectory Prediction in Autonomous Driving.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

HardFlow: Hard-Constrained Sampling for Flow-Matching Models Via Trajectory Optimization.

IEEE transactions on pattern analysis and machine intelligence·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Mar 19, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Beyond Support Samples: Incorporating Unlabeled Queries for Few-Shot Semantic Segmentation.

Yuanwei Liu, Nian Liu, Tao Jiang

IEEE Transactions on Pattern Analysis and Machine Intelligence

|March 17, 2026

Summary

This summary is machine-generated.

Few-shot semantic segmentation (FSS) is improved by Unlabeled Query Integration Few-Shot Segmentation (UQI-FSS). This method uses unlabeled query images to create a more comprehensive category representation, enhancing segmentation accuracy.

More Related Videos

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

Related Experiment Videos

Last Updated: Mar 19, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

Area of Science:

Computer Vision
Machine Learning
Artificial Intelligence

Background:

Few-shot semantic segmentation (FSS) faces challenges with intra-class diversity due to limited annotated support data.
Increasing annotated support images is impractical for few-shot learning frameworks.

Purpose of the Study:

To enhance FSS accuracy by incorporating unlabeled query images for a more comprehensive category representation.
To address the challenge of category bias in FSS using unlabeled data.

Main Methods:

Proposed Unlabeled Query Integration Few-Shot Segmentation (UQI-FSS) framework.
Developed an Unlabeled Query Integration Network (UQINet) to adaptively process unlabeled query images.
Introduced Information Bridging, Query Fusion, and Adaptive Selection Modules within UQINet.

Main Results:

UQINet adaptively extracts beneficial information and suppresses detrimental information from unlabeled query images.
Significant performance improvements demonstrated over existing methods on FSS benchmarks.
Versatility and practical value confirmed across four challenging segmentation scenarios.

Conclusions:

UQI-FSS effectively leverages unlabeled query images to overcome limitations in few-shot semantic segmentation.
The proposed UQINet architecture enhances segmentation accuracy and adaptability.
This approach offers a practical solution for improving FSS in diverse applications.