MIRACLE: An Online, Explainable Multimodal Interactive Concept Learning System

Ansel Blume, Khanh Duy Nguyen, Zhenhailong Wang, Yangyi Chen, Michal Shlapentokh-Rothman, Xiaomeng Jin, Jeonghwan Kim, Zhen Zhu, Jiateng Liu, Kuan Hao Huang, Mankeerat Sidhu, Xuanming Zhang, Vivian Liu, Raunak Sinha, Te Lin Wu, Abhay Zala, Elias Stengel-Eskin, Da Yin, Yao Xiao, Utkarsh MallZhou Yu, Kai Wei Chang, Camille Cobb, Karrie Karahalios, Lydia Chilton, Mohit Bansal, Nanyun Peng, Carl Vondrick, Derek Hoiem, Heng Ji

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present MIRACLE, a system for online, interpretable visual concept and video action recognition. Through a chat interface, users query the recognition system with an uploaded image or video. For images, MIRACLE returns concept predictions from its structured knowledge base, justifying its predictions with heatmaps and natural language-based attribute detections. For videos, MIRACLE predicts an action and justifies its prediction with time varying entity-entity relations. With its ability to learn new concepts in an online, few-shot manner and its support of dynamic changes to its knowledge base, MIRACLE represents a step forward in interpretable multimodal learning systems.

Original languageEnglish (US)
Title of host publicationMM 2024 - Proceedings of the 32nd ACM International Conference on Multimedia
PublisherAssociation for Computing Machinery
Pages11252-11254
Number of pages3
ISBN (Electronic)9798400706868
DOIs
StatePublished - Oct 28 2024
Event32nd ACM International Conference on Multimedia, MM 2024 - Melbourne, Australia
Duration: Oct 28 2024Nov 1 2024

Publication series

NameMM 2024 - Proceedings of the 32nd ACM International Conference on Multimedia

Conference

Conference32nd ACM International Conference on Multimedia, MM 2024
Country/TerritoryAustralia
CityMelbourne
Period10/28/2411/1/24

Keywords

  • few-shot learning
  • interpretability
  • multimodal interaction
  • object recognition
  • online learning
  • video action detection

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction
  • Software

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