ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1601.03896
19
363

Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures

15 January 2016
Raffaella Bernardi
Ruken Cakici
Desmond Elliott
Aykut Erdem
Erkut Erdem
Nazli Ikizler-Cinbis
Frank Keller
A. Muscat
Barbara Plank
    EGVM
    VLM
ArXivPDFHTML
Abstract

Automatic description generation from natural images is a challenging problem that has recently received a large amount of interest from the computer vision and natural language processing communities. In this survey, we classify the existing approaches based on how they conceptualize this problem, viz., models that cast description as either generation problem or as a retrieval problem over a visual or multimodal representational space. We provide a detailed review of existing models, highlighting their advantages and disadvantages. Moreover, we give an overview of the benchmark image datasets and the evaluation measures that have been developed to assess the quality of machine-generated image descriptions. Finally we extrapolate future directions in the area of automatic image description generation.

View on arXiv
Comments on this paper