# Know2Look: Commonsense Knowledge for Visual Search

arXiv: https://arxiv.org/abs/1909.00749 · HTML: https://mlsanity.com/paper/1909.00749/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Sep 2019.

## Built on by (most cited first, 1 of 1)

- [Conditional set generation using Seq2seq models](https://mlsanity.com/paper/2205.12485/) (2022)

## Abstract (arXiv)

With the rise in popularity of social media, images accompanied by contextual text form a huge section of the web. However, search and retrieval of documents are still largely dependent on solely textual cues. Although visual cues have started to gain focus, the imperfection in object/scene detection do not lead to significantly improved results. We hypothesize that the use of background commonsense knowledge on query terms can significantly aid in retrieval of documents with associated images. To this end we deploy three different modalities - text, visual cues, and commonsense knowledge pertaining to the query - as a recipe for efficient search and retrieval.