Segment-Phrase Table for Semantic Segmentation, Visual Entailment and Paraphrasing

@article{Izadinia2015SegmentPhraseTF,
  title={Segment-Phrase Table for Semantic Segmentation, Visual Entailment and Paraphrasing},
  author={Hamid Izadinia and Fereshteh Sadeghi and Santosh Kumar Divvala and Hannaneh Hajishirzi and Yejin Choi and Ali Farhadi},
  journal={2015 IEEE International Conference on Computer Vision (ICCV)},
  year={2015},
  pages={10-18}
}
  • Hamid Izadinia, Fereshteh Sadeghi, +3 authors Ali Farhadi
  • Published 2015
  • Computer Science
  • 2015 IEEE International Conference on Computer Vision (ICCV)
  • We introduce Segment-Phrase Table (SPT), a large collection of bijective associations between textual phrases and their corresponding segmentations. Leveraging recent progress in object recognition and natural language semantics, we show how we can successfully build a high-quality segment-phrase table using minimal human supervision. More importantly, we demonstrate the unique value unleashed by this rich bimodal resource, for both vision as well as natural language understanding. First, we… CONTINUE READING

    Figures, Tables, and Topics from this paper.

    Explore key concepts

    Links to highly relevant papers for key concepts in this paper:

    Citations

    Publications citing this paper.
    SHOWING 1-10 OF 16 CITATIONS

    Detecting Unseen Visual Relations Using Analogies

    VIEW 1 EXCERPT
    CITES METHODS

    A Continuously Growing Dataset of Sentential Paraphrases

    VIEW 2 EXCERPTS
    CITES BACKGROUND

    Reasoning About Fine-Grained Attribute Phrases Using Reference Games

    VIEW 1 EXCERPT
    CITES BACKGROUND

    Estimating the information gap between textual and visual representations

    Improving Event Extraction via Multimodal Integration

    VIEW 2 EXCERPTS
    CITES BACKGROUND

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 44 REFERENCES

    From captions to visual concepts and back

    VIEW 1 EXCERPT

    A Survey of Paraphrasing and Textual Entailment Methods

    VIEW 3 EXCERPTS
    HIGHLY INFLUENTIAL

    VisKE: Visual knowledge extraction and question answering by visual verification of relation phrases

    VIEW 2 EXCERPTS

    Deep Visual-Semantic Alignments for Generating Image Descriptions

    • A. Karpathy, Li Fei-Fei
    • Computer Science, Medicine
    • IEEE Transactions on Pattern Analysis and Machine Intelligence
    • 2017
    VIEW 1 EXCERPT

    Grounded Compositional Semantics for Finding and Describing Images with Sentences

    VIEW 1 EXCERPT

    Show and tell: A neural image caption generator

    VIEW 1 EXCERPT

    Enriching Visual Knowledge Bases via Object Discovery and Segmentation

    VIEW 1 EXCERPT