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: Mar 18, 2026

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing
06:25

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Published on: February 23, 2024

1.2K

Few-Shot Action Recognition via Intra- and Inter-Video Information Maximization.

Huabin Liu, Tieyuan Chen, Yuxi Li

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |March 16, 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

    Retraction notice to "Algorithm developed for dynamic quantification of coal consumption for and emission from rural winter heating" [Sci. Total Environ. 737 (2020) 139762].

    The Science of the total environment·2026
    Same author

    First trimester, one-tube screening for pregnancy complications via placental biomarkers.

    BMC pregnancy and childbirth·2026
    Same author

    Mechanism Through Which Antioxidant Polysaccharide from <i>Tetrastigma hemsleyanum</i> Protects Against DSS-Induced Ulcerative Colitis: Insights from Multi-Omics.

    Molecules (Basel, Switzerland)·2026
    Same author

    Rehmannioside D prevents estrogen-deficiency induced osteoporosis by interacting with c-Jun to dismantle the AP-1 complex and suppress MAPK/NF-κB signaling.

    Phytomedicine : international journal of phytotherapy and phytopharmacology·2026
    Same author

    Identification and Functional Analysis of a Novel NSD2 Missense Variant in a Patient With Rauch-Steindl Syndrome.

    Molecular genetics & genomic medicine·2026
    Same author

    Naringin targets TGF-β1-mediated angiogenesis to enhance the osteogenic effect of induced membrane.

    Bone & joint research·2026
    Same journal

    Relation DETR+: Exploring Explicit Position Relation Prior for Dense Prediction.

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

    RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning.

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

    CAFE: Cross-View Adaptive Fusion and Cluster Center Enhancement for Robust Multi-View Clustering.

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

    DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving.

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

    Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving.

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

    Learning Shape Anchors for Holistic Indoor Scene Understanding.

    IEEE transactions on pattern analysis and machine intelligence·2026
    See all related articles

    This study introduces Video Information Maximization (VIM) to improve few-shot action recognition by better using intra-video and inter-video data. VIM enhances how videos are sampled and aligns actions for more accurate recognition.

    Area of Science:

    • Computer Science
    • Artificial Intelligence
    • Machine Learning

    Background:

    • Few-shot action recognition leverages intra-video and inter-video information.
    • Current methods inadequately exploit these information sources, leading to reduced efficiency and inaccurate relationships.
    • Jointly considering both inter- and intra-video information is underexplored.

    Purpose of the Study:

    • To propose a novel framework, Video Information Maximization (VIM), for few-shot video action recognition.
    • To enhance the utilization of intra-video information through adaptive sampling.
    • To improve the precision of inter-video information measurement via action alignment.

    Main Methods:

    • VIM employs an adaptive spatial-temporal video sampler to select important frames and regions.

    Related Experiment Videos

    Last Updated: Mar 18, 2026

    Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing
    06:25

    Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

    Published on: February 23, 2024

    1.2K
  • A spatial-temporal action alignment model is used for feature-level alignment.
  • A new training objective based on mutual information maximizes both intra- and inter-video information.

    • Main Results:

    • The adaptive sampler preserves critical action information and reduces interference.
    • Action alignment enables more precise inter-video similarity measurements.
    • Experimental results on public datasets demonstrate VIM's effectiveness.

    Conclusions:

    • VIM effectively maximizes intra- and inter-video information for few-shot action recognition.
    • The proposed methods address limitations in current action recognition techniques.
    • VIM offers a promising direction for advancing few-shot video understanding.