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 Concept Videos

Segregation in Fresh Concrete01:16

Segregation in Fresh Concrete

Segregation in fresh concrete is a phenomenon where the components of the concrete mix separate, leading to uneven distribution and compromised structural integrity. This separation typically occurs when concrete is subjected to excessive horizontal movement within forms, or when it is dropped from considerable heights or forced through narrow, winding paths. As a result, heavier coarse aggregate particles settle at the bottom, while lighter, finer materials such as cement and water rise to the...
Gestalt Principles of Perception01:21

Gestalt Principles of Perception

Gestalt principles provide a framework for understanding how humans perceive objects as unified wholes within their context. These principles are essential in explaining the cognitive processes that make sense of complex visual stimuli by organizing them into coherent groups. One fundamental principle is proximity, which posits that objects located close to each other are perceived as a collective group. For instance, when dots are positioned near one another, the visual system interprets them...

You might also read

Related Articles

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

Sort by
Same authorSame journal

LoRASculpt: Harmonious Low-Rank Adaptation for Multimodal Large Language Models.

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

Towards clinical-level interpretation of dental panoramic radiography using an instance-guided vision-language model.

Nature biomedical engineering·2026
Same author

Systemic immune-inflammation index predicts post-thrombectomy outcomes and reveals a mediating role in the association between neurocardiac stress and prognosis: a multicenter study.

Frontiers in neurology·2026
Same author

Holistic Invariant Retracing for Distortion-Resilient Multi-Modal Learning in Spatial Transcriptomics.

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

Differentiable Clustering Graph Convolutional Network for Hyperspectral Unmixing: Methodology and Benchmark.

IEEE transactions on neural networks and learning systems·2026
Same author

MUP-SAM: Multi-scale vision mamba UNet prompt generation for SAM in multi-organ medical image segmentation.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Raising the Bar in Graph OOD Generalization: Invariant Learning beyond Explicit Environment Modeling.

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

Linearly Solving Robust Rotation Estimation.

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

Adapting Dense Vision-Language Relationships for Multi-label Classification with Partial Label.

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

Forensics Adapter: Unleashing CLIP for Generalizable Face Forgery Detection.

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

MoE-Enhanced Explainable Deep Manifold Transformation for Complex Data Embedding and Visualization.

IEEE transactions on pattern analysis and machine intelligence·2026
See all related articles
  1. Home
  2. High-quality Entity Segmentation And Grounding.
  1. Home
  2. High-quality Entity Segmentation And Grounding.

Related Experiment Video

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

High-Quality Entity Segmentation and Grounding.

Lu Qi, Yi-Wen Chen, Tao Zhang

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |May 29, 2026

    View abstract on PubMed

    Summary
    This summary is machine-generated.

    We introduce ESG, a novel pipeline for high-quality entity segmentation and grounding. ESG improves mask accuracy and semantic understanding, outperforming existing methods on diverse tasks.

    More Related Videos

    Automated Analysis of C. elegans Fluorescence Images using SegElegans
    06:27

    Automated Analysis of C. elegans Fluorescence Images using SegElegans

    Published on: October 10, 2025

    Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
    06:48

    Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

    Published on: January 7, 2019

    Related Experiment Videos

    From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
    12:08

    From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

    Published on: August 13, 2014

    Automated Analysis of C. elegans Fluorescence Images using SegElegans
    06:27

    Automated Analysis of C. elegans Fluorescence Images using SegElegans

    Published on: October 10, 2025

    Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
    06:48

    Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

    Published on: January 7, 2019

    Area of Science:

    • Computer Vision
    • Artificial Intelligence
    • Machine Learning

    Background:

    • Class-agnostic segmentation is crucial for generalizing object localization to new data.
    • Existing methods often lack boundary accuracy and semantic understanding.
    • Human-interaction-assisted image editing benefits from robust segmentation.

    Purpose of the Study:

    • To propose ESG, a pipeline for high-quality entity segmentation and grounding.
    • To address limitations in mask accuracy and semantic understanding of current methods.
    • To introduce the EntitySeg dataset for training and evaluation.

    Main Methods:

    • ESG utilizes a two-stage decoupled design with CropFormer for segmentation and GELLA for language-visual grounding.
    • CropFormer generates high-quality entity segmentation masks.
  • GELLA performs noun extraction and semantic matching between text and image regions.
  • Main Results:

    • ESG demonstrates effectiveness across five tasks: entity segmentation, panoptic segmentation, open-vocabulary segmentation, referring segmentation, and panoptic localized narratives.
    • The GELLA module shows flexibility by processing masks from any segmentation framework.
    • The proposed EntitySeg dataset provides high-resolution images and quality annotations.

    Conclusions:

    • ESG achieves high-quality entity segmentation and robust grounding.
    • The decoupled design preserves mask quality and grounding robustness.
    • ESG offers a flexible solution for various segmentation and grounding tasks.