Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jun 4, 2026

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

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

Event-Aware Instructed Assistant for Referring Video Segmentation.

Jinyu Liu, Henghui Ding, Shuting He

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |June 2, 2026
    PubMed
    Summary
    This summary is machine-generated.

    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

    Predicting 1-Year Renal Outcomes in Patients with Diabetic Kidney Disease in CKD Stages 3 to 4: A Multimodal Machine Learning Approach Fusing Clinical Composites and Pathology Images.

    Research (Washington, D.C.)·2026
    Same author

    Complement C5a/C5aR1 pathway facilitates glioblastoma progression via fostering glioma stem cell-macrophage symbiosis.

    Journal of neuroinflammation·2026
    Same author

    Benzo(a)pyrene aggregating lung inflammation via inducing IL1R1 expression in asthma: Insights from network toxicology, single-cell transcriptomics, and Mendelian randomization.

    Ecotoxicology and environmental safety·2026
    Same author

    Eosinophil-derived apoptotic extracellular vesicles accelerate steatotic liver repair after ischemia/reperfusion injury through mitochondria-associated metabolic reprogramming.

    Journal of nanobiotechnology·2026
    Same author

    A Survey on 3D Gaussian Splatting Applications: Segmentation, Editing, and Generation.

    IEEE transactions on pattern analysis and machine intelligence·2026
    Same author

    XOV-Action: Towards Generalizable Open-Vocabulary Action Recognition.

    IEEE transactions on pattern analysis and machine intelligence·2026
    Same journal

    Change-Prior-Guided Unsupervised Change Detection of Heterogeneous Remote Sensing Images.

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
    Same journal

    AgonicDreamer: Enhancing Multi-View Consistency in Text-to-3D Generation via Rectified Score Distillation.

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
    Same journal

    BiCM-Prompt: Bidirectional Cross-Modal Prompt Tuning for Class-Incremental Learning on Multisource Remote Sensing Images.

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
    Same journal

    GoP-based Quality Enhancement on Video Compression.

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
    Same journal

    Align then Tensorize: Multi-Level Consistent Anchor Graph Learning for Scalable Multi-View Clustering.

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
    Same journal

    Beyond Fidelity: Diverse Image Synthesis via Retrieval-Augmented Diffusion.

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
    See all related articles

    This study introduces EVIS, an Event-Aware Video Instructed Segmentation Assistant, which decomposes videos into simple events for improved referring video segmentation. EVIS enhances understanding by processing events sequentially, reducing model confusion and hallucinations.

    Area of Science:

    • Computer Science
    • Artificial Intelligence
    • Machine Learning

    Background:

    • Current referring video segmentation models treat videos as single events, leading to complexity and potential hallucinations.
    • This approach overlooks the natural segmentation of videos into distinct, text-related events.

    Purpose of the Study:

    • To develop a novel method for referring video segmentation that addresses the limitations of existing single-event processing.
    • To improve the accuracy and reduce confusion in video segmentation by understanding content event-by-event.

    Main Methods:

    • Introducing EVIS (Event-Aware Video Instructed Segmentation Assistant) that uses text-guided Event Queries to partition videos.
    • Implementing hierarchical understanding by extracting event-aware visual-text features.

    More Related Videos

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
    04:48

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

    Published on: November 30, 2022

    Related Experiment Videos

    Last Updated: Jun 4, 2026

    Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
    08:25

    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

    Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
    04:48

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

    Published on: November 30, 2022

  • Proposing Object-Pixel-Hybrid Learning for long-term target tracking in videos by integrating pixel and object queries.

    • Main Results:

    • EVIS demonstrates strong performance across 5 public benchmarks for referring video segmentation.
    • The event-by-event processing approach effectively reduces model confusion and hallucinations.
    • Object-Pixel-Hybrid Learning enables robust tracking in long-term videos.

    Conclusions:

    • EVIS offers a more effective approach to referring video segmentation by leveraging event decomposition.
    • The proposed methods enhance the hierarchical understanding of complex video content.
    • Future work will involve releasing code and trained models for public access.