Choosing Basic-Level Concept Names Using Visual and Language Context
Abstract
We study basic-level categories for describing visual concepts, and empirically observe context-dependant basic-level names across thousands of concepts. We propose methods for predicting basic-level names using a series of classification and ranking tasks, producing the first large-scale catalogue of basic-level names for hundreds of thou-sands of images depicting thousands of visual concepts. We also demonstrate the usefulness of our method with a picture-to-word task, showing strong improvement over re-cent work by Ordonez et al, by modeling of both visual and language context. Our study suggests that a model for nam-ing visual concepts is an important part of any automatic image/video captioning and visual story-telling system. 1.
Cite
Text
Mathews et al. "Choosing Basic-Level Concept Names Using Visual and Language Context." IEEE/CVF Winter Conference on Applications of Computer Vision, 2015. doi:10.1109/WACV.2015.85Markdown
[Mathews et al. "Choosing Basic-Level Concept Names Using Visual and Language Context." IEEE/CVF Winter Conference on Applications of Computer Vision, 2015.](https://mlanthology.org/wacv/2015/mathews2015wacv-choosing/) doi:10.1109/WACV.2015.85BibTeX
@inproceedings{mathews2015wacv-choosing,
title = {{Choosing Basic-Level Concept Names Using Visual and Language Context}},
author = {Mathews, Alexander Patrick and Xie, Lexing and He, Xuming},
booktitle = {IEEE/CVF Winter Conference on Applications of Computer Vision},
year = {2015},
pages = {595-602},
doi = {10.1109/WACV.2015.85},
url = {https://mlanthology.org/wacv/2015/mathews2015wacv-choosing/}
}