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

Facial Feedback Hypothesis01:24

Facial Feedback Hypothesis

546
Charles Darwin proposed that facial expressions are an evolutionary adaptation for communication. He argued that these expressions are not influenced by culture but are universal across species. For example, a snarling expression with exposed teeth signals a threat in many animals, including humans. Darwin also suggested that displaying an emotion can intensify the feeling. Smiling, for example, could enhance one's sense of happiness. This idea laid the foundation for understanding the role...
546
Association Areas of the Cortex01:21

Association Areas of the Cortex

8.7K
Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
8.7K
Muscles for Facial Expressions01:14

Muscles for Facial Expressions

4.6K
The craniofacial muscles are a collection of approximately 20 thin skeletal muscles situated beneath the skin of the face and scalp. These muscles, primarily responsible for the vast array of human facial expressions, originate from the bones or fibrous structures of the skull and extend outwards to connect with the skin. While most skeletal muscles in the body are enveloped in thick fascia, facial muscles generally have a more delicate fascial covering, with the buccinator muscle being a...
4.6K
Modeling and Similitude01:12

Modeling and Similitude

588
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
588
Extraction: Advanced Methods00:56

Extraction: Advanced Methods

1.1K
Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
1.1K
Shape and Texture of Coarse Aggregate01:25

Shape and Texture of Coarse Aggregate

651
Aggregate shape is classified based on the relative sharpness or roundness of the edges and corners. This classification includes categories like rounded, angular, elongated, and flaky, each with specific characteristics. Rounded aggregates, fully shaped by attrition, are typical of river or seashore gravel, while angular aggregates, such as crushed rock, have well-defined edges. Aggregates that are elongated and flaky are less desirable, as they can reduce the workability and strength of...
651

You might also read

Related Articles

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

Sort by
Same author

GRLT: Learning more from teachers by rethinking knowledge distillation from GNNs to MLPs.

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

A Method for Data Augmentation in Vertical Federated Learning Addressing Data Heterogeneity.

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

Hierarchical Causal Learning for Face Age Synthesis.

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

GBFRS: Robust Fuzzy Rough Sets via Granular Ball Computing.

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

Decoding epigenetic aging using plants: lessons from Arabidopsis thaliana as a short-lived model.

Science bulletin·2026
Same author

Aging drives a program of DNA methylation decay in plant organs.

Science (New York, N.Y.)·2026
Same journal

A Survey on Human-Centric Voice-Face Multimodal Learning.

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

Vision-Assisted Foundation Model for Solving Multitask Vehicle Routing Problems.

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

FP3O: Enabling Proximal Policy Optimization in Multiagent Cooperation With Parameter-Sharing Versatility.

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

Hierarchical Semantic Concept Modeling for Generalizable Myocardial Pathology Segmentation on Multisequence CMR Images.

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

Stability of Time-Varying Impulsive Systems With State-Dependent Delay and Its Application in Complex Networks.

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

Adaptive Learning Control of Uncertain Systems via Weight and Intrinsic Plasticity-Based Neural Networks.

IEEE transactions on neural networks and learning systems·2026
See all related articles
  1. Home
  3. Fdsrm: A Feature-driven Style-agnostic Foundation Model For Sketch-less Facial Image Retrieval.
  1. Home
  3. Fdsrm: A Feature-driven Style-agnostic Foundation Model For Sketch-less Facial Image Retrieval.

Related Experiment Video

Author Spotlight: Enhancing Skin Model Diversity with Cost-Effective 3D Cellular Models
08:32

Author Spotlight: Enhancing Skin Model Diversity with Cost-Effective 3D Cellular Models

Published on: October 20, 2023

3.8K

FDSRM: A Feature-Driven Style-Agnostic Foundation Model for Sketch-Less Facial Image Retrieval.

Yingge Liu, Dawei Dai, Shuyin Xia

    IEEE Transactions on Neural Networks and Learning Systems
    |November 25, 2025

    View abstract on PubMed

    Summary
    This summary is machine-generated.

    This study introduces a feature-driven foundation model for sketch-less facial image retrieval (FDSRM). The novel approach enhances accuracy and generalization by addressing sketch style diversity and stroke randomness.

    More Related Videos

    Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm
    09:49

    Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

    Published on: December 24, 2015

    14.5K
    Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
    07:34

    Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

    Published on: June 3, 2013

    17.8K

    Related Experiment Videos

    Author Spotlight: Enhancing Skin Model Diversity with Cost-Effective 3D Cellular Models
    08:32

    Author Spotlight: Enhancing Skin Model Diversity with Cost-Effective 3D Cellular Models

    Published on: October 20, 2023

    3.8K
    Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm
    09:49

    Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm

    Published on: December 24, 2015

    14.5K
    Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
    07:34

    Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

    Published on: June 3, 2013

    17.8K

    Area of Science:

    • Computer Vision
    • Artificial Intelligence
    • Human-Computer Interaction

    Background:

    • Traditional sketch-less facial image retrieval (SLFIR) struggles with diverse sketching styles and stroke placement.
    • Existing methods often require high-quality sketch inputs, limiting practical application.

    Purpose of the Study:

    • To develop a novel feature-driven foundation model for sketch-less facial image retrieval (FDSRM).
    • To create a model robust to variations in sketch style and stroke randomness.
    • To improve the accuracy and generalization capabilities of SLFIR systems.

    Main Methods:

    • Proposed a feature-driven foundation model (FDSRM) with a feature observer module (FOM) and adaptive fusion adapter (AFA).
    • FOM utilizes multiple experts to extract style-invariant features from sketches.
  • AFA dynamically adjusts feature fusion based on sketch stroke progression, incorporating sketching priors.
  • Employed a facial image-text alignment pretraining (FAIP) model for enhanced robustness.

    • Main Results:

    • FDSRM demonstrates significant advantages in early retrieval accuracy.
    • The model exhibits superior system generalization capabilities across multi-style scenarios.
    • Achieved state-of-the-art performance in both qualitative and quantitative evaluations without auxiliary information.

    Conclusions:

    • The proposed FDSRM effectively addresses the challenges of sketch style diversity and stroke randomness in SLFIR.
    • The feature-driven approach enhances retrieval accuracy and robustness, outperforming existing methods.
    • This work advances the field of sketch-less facial image retrieval, offering a more practical and versatile solution.